CN116908474A - Biomarker related to atrial fibrillation and application thereof - Google Patents

Biomarker related to atrial fibrillation and application thereof Download PDF

Info

Publication number
CN116908474A
CN116908474A CN202310904029.1A CN202310904029A CN116908474A CN 116908474 A CN116908474 A CN 116908474A CN 202310904029 A CN202310904029 A CN 202310904029A CN 116908474 A CN116908474 A CN 116908474A
Authority
CN
China
Prior art keywords
biomarker
atrial fibrillation
a0a024r930
a0a024r462
a0a024r0t9
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310904029.1A
Other languages
Chinese (zh)
Inventor
谢博洽
李丽娜
苏丕雄
杨敏福
刘兴鹏
高杰
郭玉林
张文谦
刘晓艳
赵蕾
张叶萍
王怡丹
华存存
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Chaoyang Hospital
Original Assignee
Beijing Chaoyang Hospital
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Chaoyang Hospital filed Critical Beijing Chaoyang Hospital
Priority to CN202310904029.1A priority Critical patent/CN116908474A/en
Publication of CN116908474A publication Critical patent/CN116908474A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/62Detectors specially adapted therefor
    • G01N30/72Mass spectrometers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6848Methods of protein analysis involving mass spectrometry
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N2030/022Column chromatography characterised by the kind of separation mechanism
    • G01N2030/027Liquid chromatography
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00Detection or diagnosis of diseases
    • G01N2800/32Cardiovascular disorders
    • G01N2800/326Arrhythmias, e.g. ventricular fibrillation, tachycardia, atrioventricular block, torsade de pointes

Abstract

The application relates to the technical field of molecular diagnosis, in one aspect relates to a biomarker related to atrial fibrillation, which comprises the following components: one or more of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697; in another aspect, the application relates to the use of a biomarker in the manufacture of a diagnostic product for detecting atrial fibrillation. The P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697 proteins provided by the application are used as biomarkers for atrial fibrillation diagnosis, have higher phase difference than the traditional circulating biomarkers, can be used for preparing diagnostic products for detecting atrial fibrillation, are beneficial to reducing the risk of ischemic stroke of atrial fibrillation patients, improve prognosis, and have important clinical significance.

Description

Biomarker related to atrial fibrillation and application thereof
Technical Field
The application relates to the technical field of molecular diagnosis, in particular to a biomarker related to atrial fibrillation and application thereof.
Background
At present, the number of cardiovascular diseases in China is up to 2.9 hundred million, and the death rate is higher than that of tumors and other diseases and accounts for more than 40% of resident disease death. Atrial Fibrillation (AF) is the most common arrhythmia in clinic, the overall incidence of the population is around 1%, and with age, the incidence of atrial fibrillation is increasing, up to 10% of people over 75 years old. AF-related atrial dysfunction can cause serious complications such as cerebral apoplexy and heart failure. Because the pathogenesis of atrial fibrillation is not completely elucidated, the main treatment strategy of AF is to prevent and treat complications such as thrombus, but even in standardized anticoagulation treatment, the incidence rate of cerebral apoplexy of AF patients is far higher than that of control people. Therefore, AF is found in time, and targeted diagnosis and treatment measures are taken to prevent atrial fibrillation, relapse and improve treatment.
Traditional circulating biomarkers such as Brain Natriuretic Peptide (BNP), inflammatory markers including C-reactive protein (CRP), interleukin-6 (IL-6), etc. play an important role in diagnosis and prognosis evaluation of AF, which, although highly sensitive, are relatively low in specificity due to their easy detection in non-AF patients such as heart failure or myocardial infarction patients. Therefore, the pathogenesis of AF is explored, a more specific biomarker is searched, and the target population with high risk of atrial fibrillation can be more locked, so that strict screening is performed, and the method is a key for improving treatment and prognosis of AF patients.
Disclosure of Invention
It is a first object of the present application to provide biomarkers related to atrial fibrillation that can be used as biomarkers for atrial fibrillation detection.
A second object of the present application is to provide the use of a biomarker for the preparation of a diagnostic product for the detection of atrial fibrillation.
With the development of proteomic analysis techniques, the discovery and validation of biomarkers will progress greatly. Data independent DIA represents a significant advance in protein quantification and is significant due to its ability to perform high throughput quantitative proteomics. Non-targeted DIA shows great potential in comprehensively revealing and validating predictive and prognostic candidate biomarkers for various diseases.
According to the application, differential expression proteins between atrial fibrillation patients and coronary heart disease patients are identified and screened through a proteomics method DIA, and the high-expression P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697 proteins exist in epicardial adipose tissues of the DIA patients, ROC analysis is carried out, and the overall prediction accuracy of 6 proteins serving as atrial fibrillation biomarkers is evaluated through AUC analysis; ELISA method is used for verifying that the differential protein selects the blood plasma of peripheral blood and atrial blood of atrial fibrillation patients and healthy volunteers for ELISA verification, and the quantitative verification of the ELISA method has good consistency with DIA results.
In a first aspect of the application, there is provided a biomarker associated with atrial fibrillation, the biomarker comprising: one or more of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697.
In a second aspect of the application there is provided the use of a biomarker in the manufacture of a diagnostic product for detecting atrial fibrillation, the biomarker comprising: one or more of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697.
Preferably, the diagnostic product comprises: detection chip, detection reagent or detection kit.
Preferably, the biomarker is P00491.
Preferably, the biomarker is A0a024R462.
Preferably, the biomarker is P02776.
Preferably, the biomarker is A0a024R0T9.
Preferably, the biomarker is A0a024R930.
Preferably, the biomarker is P08697.
Preferably, the biomarker is P08697.
Preferably, the biomarker is any two combinations of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697.
Preferably, the biomarker is any three combinations of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697.
Preferably, the biomarker is any four combinations of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697.
Preferably, the biomarker is any five combinations of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697.
Preferably, the biomarkers are P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, and P08697.
Preferably, the detection refers to detection of a subject's peripheral blood, atrial blood, or an isolated epicardial adipose tissue sample.
Preferably, the assay is an assay to detect the level of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697 protein expression in epicardial adipose tissue of a subject ex vivo.
Preferably, the AUC value is used as a criterion for diagnosing atrial fibrillation when detecting biomarkers in isolated epicardial adipose tissue of a subject;
when the biomarker is P00491, the AUC value is not less than 0.9412;
when the biomarker is A0A024R462, the AUC value is not lower than 0.9034;
when the biomarker is P02776, the AUC value is not less than 0.8655;
when the biomarker is A0A024R0T9, the AUC value is not lower than 0.8067;
when the biomarker is A0A024R930, the AUC value is not lower than 0.8067;
when the biomarker is P08697, the AUC value is not less than 0.8277;
the biomarker is P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, and P08697 when combined, the AUC value is not less than 0.987.
Preferably, the assay is an assay to detect the level of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697 protein expression in the plasma, serum or blood of a subject; more preferably, the assay is an assay to detect the expression level of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697 protein in the plasma of a subject.
Preferably, the biomarker predictive accuracy is assessed by detecting the presence of high expression of the biomarker in the subject, while performing a ROC curve statistical analysis, and by AUC analysis.
Preferably, the biomarker is detected in the plasma of the peripheral blood of the subject with an AUC value of between 0.5771 and 0.8910.
Preferably, the AUC value is used as a criterion for diagnosing atrial fibrillation when detecting biomarkers in the plasma of the peripheral blood of a subject;
when the biomarker is P00491, the AUC value is not less than 0.5771;
when the biomarker is A0A024R462, the AUC value is not lower than 0.7264;
when the biomarker is P02776, the AUC value is not less than 0.6083;
when the biomarker is A0A024R0T9, the AUC value is not lower than 0.7431;
when the biomarker is A0A024R930, the AUC value is not lower than 0.8910;
when the biomarker is P08697, the AUC value is not less than 0.6847;
the biomarker is P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, and P08697 when combined, the AUC value is not less than 0.934.
Preferably, the biomarker is detected in the plasma of the subject's atrial blood with an AUC value between 0.7208 and 0.8471.
Preferably, the AUC value is used as a criterion for diagnosing atrial fibrillation when detecting biomarkers in the plasma of the subject's atrial blood;
when the biomarker is P00491, the AUC value is not less than 0.7208;
when the biomarker is A0A024R462, the AUC value is not lower than 0.7375;
when the biomarker is P02776, the AUC value is not less than 0.7667;
when the biomarker is A0A024R0T9, the AUC value is not lower than 0.8188;
when the biomarker is A0A024R930, the AUC value is not lower than 0.8417;
when the biomarker is P08697, the AUC value is not less than 0.7177;
the biomarker is P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697, and the AUC is not less than 0.904 when combined.
The beneficial effects are that:
the P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697 proteins provided by the application are used as biomarkers for atrial fibrillation diagnosis, have higher phase difference than the traditional circulating biomarkers, can be used for preparing diagnostic products for detecting atrial fibrillation, are beneficial to reducing the risk of ischemic stroke of atrial fibrillation patients, improve prognosis, and have important clinical significance.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a functional profile of an identified total protein, wherein FIG. 1A is a histogram of GO annotation results; FIG. 1B is a diagram of a COG functional classification cluster; FIG. 1C is a KEGG pathway annotation diagram; FIG. 1D is an IPR annotation diagram;
FIG. 2 is a principal component analysis chart of PCA;
FIG. 3 is a volcanic plot of proteins showing differential expression of proteins in the AF and CAD groups; proteins with statistical differences (. Gtoreq.1.2 times, P < 0.05) are in the upper right and upper left quadrants;
FIG. 4 is a graph of relative protein content cluster heat of differential expression;
FIG. 5 is an enrichment analysis graph of differentially expressed proteins in AF and CAD groups, wherein FIG. 5A is a GO enrichment histogram; FIG. 5B is a KEGG pathway enriched bubble diagram; FIG. 5C is a domain enrichment bubble map;
FIG. 6 is a graph of EAT proteomics ROC of selected differentially expressed secreted proteins;
FIG. 7 is a graph showing quantitative measurement of the difference in the expression of 6 secreted proteins in peripheral blood of 30 healthy volunteers and peripheral blood and atrial blood plasma of 48 patients with atrial fibrillation by ELISA;
FIG. 8 is a graph of plasma ROC of selected differentially expressed secreted proteins.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular forms also include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
The technical solutions of the present application will be clearly and completely described in connection with the embodiments, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Examples
1. Experimental major reagent and manufacturer name
The iRT kit is available from Biognosys; the Bradford protein quantification kit was purchased from bi cloud; dithiothreitol DTT, available from Sigma company (cat No. D9163-25G); iodoacetamide IAM, purchased from Sigma (cat. I6125-25G); dodecyl sulfate, SDS, purchased from chinese drug groups; urea is purchased from the national drug group (cat 10023218); mass spectrum grade pancreatin was purchased from Promega company (cat No. V5280); ammonium bicarbonate was purchased from Sigma (cat No. 5330050050); LC-MS grade ultrapure water was purchased from Thermo Fisher Chemical (cat# W6-4); triethylammonium bicarbonate buffer TEAB, available from Sigma company (cat# T7408-500 ML); LC-MS grade acetonitrile was purchased from Thermo Fisher Chemical company (cat No. A955-4); LC-MS grade formic acid was purchased from Thermo Fisher Scientific (cat. A117-50); acetone was purchased from beijing chemical plant (commodity number 11241203810051); ammonia was purchased from Sigma (cat. No. 221228-500 ML-A) ProteoMiner low abundance protein enrichment kit was purchased from Bio-Rad (cat No. 1633007), and trifluoroacetic acid TFA was purchased from Sigma (cat. T6508-100 ML).
2. Experimental method
1. Patient entry group
Hospitalized patients belonging to heart center of Beijing Kogyo hospital at the university of first medical science of 2 months 2021 to 3 months 2022 were selected, wherein 14 patients with persistent atrial fibrillation and 16 patients with coronary heart disease were selected. This study was approved by the medical ethics committee of the university of capital medical science affiliated to the Beijing facing yang hospital. All enrolled atrial fibrillation patients and healthy volunteers signed informed consent. All procedures performed in this study involving human participants were in compliance with the declaration of helsinki. Wherein the AF patient is subjected to surgical atrial fibrillation hybridization operation, and the coronary heart disease patient is subjected to coronary artery bypass grafting operation. Epicardial Adipose Tissue (EAT) was left during surgery and rapidly cooled with liquid nitrogen, after which it was transferred to-80 ℃ refrigerator for preservation. The disease state reflected by the histology around the lesion of the selected patient is more realistic and has fewer interference factors.
To ensure homogeneity in the patient, bias caused by abnormal cardiac metabolism due to the combination of other diseases is eliminated, and the following criteria are selected: (1) Patients with clinically definite atrial fibrillation, but not receiving radiofrequency ablation; (2) Without history of myocardial infarction, myocardial infarction can be excluded from the related examination; (3) No valvular heart disease, no idiopathic cardiomyopathy, and no other types of arrhythmia; (4) Not receiving any surgical or interventional treatment for cardiovascular disease; (5) no heart failure symptom, and the left ventricular ejection fraction is more than or equal to 50%; (6) Related examinations exclude systemic inflammatory or infectious diseases; (7) no history of malignancy; (8) no significant other systemic disease; (9) unstable clinical conditions.
2. Sample preparation
2.1 Total protein extraction
Taking out a tissue sample from a refrigerator at the temperature of minus 80 ℃, grinding the tissue sample into powder at low temperature, rapidly transferring the powder to a centrifuge tube precooled by liquid nitrogen, adding a proper amount of PASP protein lysate (100 mM ammonium bicarbonate and 8M urea pH=8), oscillating and uniformly mixing, and performing ice water bath ultrasonic treatment for 5min for full lysis. Centrifugation was performed at 12000g for 15min at 4℃and 10mM DTT was added to the supernatant and reacted at 56℃for 1h, followed by addition of a sufficient amount of IAM and reaction at room temperature in the dark for 1h. Adding 4 times of pre-cooled acetone at-20deg.C for precipitating for at least 2 hr, centrifuging at 4deg.C and 12000g for 15min, and collecting precipitate. Afterwards, 1mL-20 ℃ pre-chilled acetone is added for re-suspension and the precipitate is washed, and the precipitate is centrifuged at 12000g for 15min at 4 ℃, collected and air-dried, and a proper amount of protein dissolving solution (8M urea, 100mM TEAB pH=8.5) is added for dissolving the protein precipitate.
2.2 protein assay
A standard BSA protein solution was prepared using the Bradford protein quantification kit according to the instructions with a concentration gradient ranging from 0 to 0.5. Mu.g/. Mu.L. BSA standard protein solutions with different concentration gradients and sample solutions to be tested with different dilution factors are respectively taken and added into a 96-well plate, the volume is complemented to 20 mu L, and each gradient is repeated for 3 times. 180 mu L G of the staining solution was rapidly added, and the solution was left at room temperature for 5min, and the absorbance at 595nm was measured. And drawing a standard curve by using the absorbance of the standard protein liquid and calculating the protein concentration of the sample to be detected. And respectively taking 20 mug protein samples to be detected, and carrying out 12% SDS-PAGE gel electrophoresis, wherein the electrophoresis conditions of the concentrated gel are 80V and 20min, and the electrophoresis conditions of the separating gel are 120V and 90min. After electrophoresis, coomassie brilliant blue R-250 is used for dyeing, and the color is decolorized until the band is clear.
2.3 proteolysis
Taking protein sample, adding DB protein solution (8M urea, 100mM TEAB, pH=8.5) to make up to 100 μl, adding pancreatin and 100mM TEAB buffer, mixing, enzyme cutting at 37deg.C for 4 hr, adding pancreatin and CaCl 2 And (5) enzyme digestion overnight. Adding formic acid to adjust pH to less than 3, mixing, centrifuging at room temperature and 12000g for 5min, collecting supernatant, slowly passing through C18 desalting column, continuously cleaning with cleaning solution (0.1% formic acid and 3% acetonitrile) for 3 times, adding appropriate amount of eluent (0.1% formic acid and 70% acetonitrile), collecting filtrate, and lyophilizing.
2.4DDA Spectrum library construction
(1) Fraction separation
Mobile phase a (2% acetonitrile, 98% water, ammonia adjusted to ph=10) and B (98% acetonitrile, 2% water, ammonia adjusted to ph=10) were prepared. The mixed lyophilized powder was dissolved in solution A and centrifuged at 12000g for 10min at room temperature. Using an L-3000HPLC system, the column was Waters BEH C18 (4.6X105 mm,5 μm) and the column temperature was set to 45℃with the specific elution gradient shown in Table 1.1 tube per minute was collected and combined into 4 fractions, each of which was dissolved by adding 0.1% formic acid after lyophilization.
TABLE 1 liquid chromatography elution gradient table for polypeptide fraction separation
Time (min) Flow rate (mL/min) Mobile phase a (%) Mobile phase B (%)
0 1 97 3
10 1 95 5
20 1 80 20
27 1 60 40
29 1 50 50
30 1 30 70
35 1 0 100
(2) DDA mode liquid quality detection
Mobile phase a (100% water, 0.1% formic acid) and B (80% acetonitrile, 0.1% formic acid) were prepared. 4. Mu.g of the supernatant was added to each fraction, 0.8. Mu.l of iRT reagent was added, and then half of the volume of each fraction was sampled and examined by a machine. Using EASY-nLC TM The 1200 nm upgrade UHPLC system, the pre-column was a homemade pre-column (4.5 cm. Times.75 μm,3 μm), the analytical column was a homemade analytical column 15 cm. Times.150 μm,1.9 μm) and the liquid chromatography elution conditions are shown in Table 2. Using Q exact TM Serial mass spectrometer, nanospray Flex TM (ESI) ion source, ion spray voltage of 2.1kV, ion transmission tube temperature of 320 ℃, mass spectrum adopting Data Dependent Acquisition (DDA) mode, mass spectrum full scanning range of 350-1500 m/z, primary mass spectrum resolution of 120000 (200 m/z), and maximum capacity of C-trap of 3×10 6 The maximum injection time of C-trap is 80ms; selecting parent ion with ion intensity TOP 40 in full scan, and performing secondary mass spectrum detection by high energy collision fragmentation (HCD) method with the resolution of 15000 (200 m/z) and maximum capacity of C-trap of 5×10 4 The maximum injection time of C-trap was 45ms, the fragmentation collision energy of the peptide fragment was set to 27%, and the threshold intensity was set to 1.1X10 4 And setting the dynamic exclusion range to be 20s, and generating mass spectrum detection original data (. Raw) for constructing a DDA spectrum chart library.
TABLE 2 liquid chromatography elution gradient table
Time (min) Flow rate (nL/min) Mobile phase a(%) Mobile phase B (%)
0 600 95 5
1 600 92 8
76 600 70 30
81 600 50 50
82 600 5 95
92 600 5 95
92.5 600 95 5
93.5 600 95 5
94.5 600 5 95
99 600 5 95
100 600 95 5
2.5DIA mode liquid quality detection
Mobile phase a (100% water, 0.1% formic acid) and B (80% acetonitrile, 0.1% formic acid) were prepared. 4. Mu.g of the supernatant was collected for each sample, 0.8. Mu.l of iRT reagent was added thereto, and then half of the volume of each sample was collected and subjected to machine test. Using EASY-nLC TM The 1200 nm upgrade UHPLC system was pre-column (4.5 cm. Times.75 μm,3 μm) and the analytical column was self-prepared analytical column (15 cm. Times.150 μm,1.9 μm) and the liquid chromatography elution conditions were as in Table 2. Using Q exact TM Serial mass spectrometer, nanospray Flex TM (ESI) ion source, ion spray voltage is set to be 2.1kV, ion transmission tube temperature is set to be 320 ℃, mass spectrum adopts a non-data dependent acquisition mode (DIA), mass spectrum full-scanning range is set to be 350-1500 m/z, primary mass spectrum resolution is set to be 60000 (200 m/z), and maximum capacity of C-trap is set to be 5 multiplied by 10 5 The maximum injection time of C-trap is 20ms; secondary Mass Spectrometry detection Using HCD method fragmentation with resolution of 30000 (200 m/z) and maximum C-trap capacity of 1×10 6 The fragmentation collision energy of the peptide fragment was set to 27%, and mass spectrum detection was generatedRaw data (.raw).
2.6 data analysis
2.6.1 identification and quantification of proteins
Machine data in DDA scan mode was searched using search software Proteome Discoverer 2.2.2.2 (PD 2.2, thermo) from the homo sapiens uniprot 2022_1_27.Fasta (203746 sequences) protein database. The search parameters were set as follows: the mass tolerance of the precursor ions was 10ppm and the mass tolerance of the fragment ions was 0.02Da. The immobilization modification is alkylation modification of cysteine, the variable modification is methionine oxidation modification, the N end is acetylation modification, and the maximum number of the missed cleavage sites is allowed.
To improve the quality of the analysis results, the PD2.2 software further filters the search results: the spectral peptide (Peptide Spectrum Matches, PSMs for short) with the credibility of more than 99 percent is credible PSMs, the protein containing at least one unique peptide segment is credible protein, only credible spectral peptide and protein are reserved, FDR verification is carried out, and the peptide segment and protein with the FDR more than 1 percent are removed.
Importing the PD2.2 software search identification result into Spectronaut version 14.0.0 Biognosys software to generate a spectrogram library; setting peptide fragments and ion pair selection rules; selecting peptide fragments and sub-ions meeting the conditions from the spectrogram to generate a Target List; DIA data is imported, ion pair chromatographic peaks are extracted according to a Target List, sub-ion matching and peak area calculation are carried out, and simultaneous qualitative and quantitative determination of peptide fragments is achieved. The retention time correction was performed using iRT added to the sample, and the precursor ion Qvalue cutoff value was set to 0.01. Statistical analysis of protein quantification results using T-test defined as Differentially Expressed Protein (DEP) with significant differences in quantification between the experimental and control groups (p <0.05, FC > 2).
2.6.2 functional analysis of proteins and DEP
GO and IPR functional notes (including Pfam, PRINTS, proDom, SMART, proSite, PANTHER database) were performed using the interperscan software, and COG and KEGG performed functional protein family and pathway analysis on the identified proteins. Volcanic analysis, clustered heat map analysis, and GO, IPR, and KEGG pathway enrichment analysis were performed for DPE and possible protein-protein interactions were predicted using STRING DB software.
3. Human plasma sample
49 patients with AF, who received radio frequency ablation, were hospitalized in Beijing Korea hospitals affiliated to the university of capital medical science, from 8 months 2022 to 11 months 2022, were selected. Clinical data such as gender, age, BMI, smoking history, drinking history, ultrasonic index, etc. of the patient are recorded.
Inclusion criteria: (1) hospitalized patients with atrial fibrillation; (2) meets the radio frequency ablation indication, and has not been accepted by radio frequency ablation or other atrial fibrillation operation treatment in the past; (3) and signing an informed consent form.
Exclusion criteria: (1) a history of myocardial infarction; (2) merging other types of arrhythmia; (3) idiopathic cardiomyopathy; (4) surgery or interventional therapy for cardiovascular disease has been accepted in the past; (5) left ventricular ejection fraction < 50%.
We recruited a control group of 20 gender matched healthy volunteers to establish the normal range of plasma markers. Inclusion criteria are (1) history of atrial-free fibrillation; (2) history of atrial fibrillation cardiovascular disease, (3) no history of malignancy.
3.1 blood sampling and plasma separation
The patient was collected with a blood lancet and an anticoagulant tube (containing EDTA) for 5mL each of atrial blood and peripheral blood during the operation in the morning of the operation. Centrifuging at 3000rpm and 4deg.C for 10min, collecting supernatant, and storing at-80deg.C after sub-packaging with 1 mL/tube.
3.2ELISA validation
For the 6 secreted proteins detected previously, we collected plasma from the atrial and peripheral blood of 49 AF patients and 30 gender-matched healthy volunteers, validated by ELISA, and the ELISA kit is shown in table 3. In the follow-up verification, the epicardial adipose tissue is relatively difficult to obtain, the chest opening of the patient without any heart disease cannot be obtained, the blood plasma is adopted for verification, the repeatability is relatively higher, the acceptance is higher, and the operation is more convenient; furthermore, to reduce the effect of other diseases on plasma markers, we selected healthy people as control group.
Blood samples are one of the common sample types, which are easy to obtain and have minimal trauma to patients in clinic, but the operation procedures of blood samples in clinic are sometimes not suitable for biomarker discovery, because the samples may be subjected to different pretreatment, even some samples are stored in different biological sample libraries, or the packaging time, the storage time and the storage condition have slight differences, which can significantly affect the stability of metabolites. Serum and plasma metabolite species are not greatly different, and plasma has the advantage of rapid processing compared to serum, and there is no need to wait for blood to coagulate, thus better reproducibility.
(1) The reagents were equilibrated to room temperature (18-25 ℃) for at least 30min and prepared for further use.
(2) Sample adding: and respectively arranging standard substance holes and sample holes to be tested. 100 μl of standard or sample to be tested is added into each well, the mixture is gently shaken and mixed, covered with a plate patch and incubated for 2h at 37 ℃.
(3) Discard the liquid, spin-dry, and do not need washing.
(4) 100 μl of biotin-labeled antibody working solution was added to each well, and a new plate was covered and incubated at 37deg.C for 1h.
(5) The liquid in the holes is discarded, the plate is dried and washed 3 times. Soaking for 2 minutes, 200 μl/well, and spin-drying.
(6) 100 μl of horseradish peroxidase-labeled avidin working solution was added to each well, and a new plate patch was covered and incubated at 37℃for 1 hour.
(7) The liquid in the holes is discarded, the plate is dried by spin-drying and washed 5 times. Soaking for 2 minutes, 200 μl/well, and spin-drying.
(8) 90 μl of substrate solution was added to each well in sequence, and the mixture was developed at 37℃for 15-30 minutes in the absence of light.
(9) The reaction was terminated by adding 50. Mu.l of a termination solution to each well in this order. The optical density (OD value) of each well was measured sequentially with a microplate reader at a wavelength of 450nm within 5 minutes after the reaction was terminated.
Table 3 ELISA kit
3.3 statistical analysis method
Statistical analysis is carried out by using SPSS26.0 software, metering data is represented by mean ± standard (normal distribution) or median quartile distribution (bias distribution), and group comparison is carried out by adopting independent sample T test (normal distribution) or nonparametric test (bias distribution); the count data description is expressed in n (%), and the comparison between groups is tested by chi-square or Fisher exact probability. The significance level of the statistical test is equal to bilateral P <0.05 (P < 0.05; P < 0.01; P < 0.001).
4. Results
4.1 quantitative proteomic study of epicardial adipose tissue for AF and CAD
We collected data for 14 patients receiving surgical atrial fibrillation hybrid AF and 17 CAD patients receiving coronary artery bypass grafting (Table 4). Changes in protein abundance were studied using a DIA quantitative mass spectrometer.
4.2 functional Classification and pathway analysis of Total protein
We analyzed 31 EAT samples and identified 23352 polypeptides and 4541 proteins with Proteome Discoverer software [ false discovery rate <1% ]. 22544 polypeptides out of 4180 proteins were detected in total by DIA-MS analysis. The complete dataset is then classified according to the evolutionary relationship protein analysis (Panther) classification scheme. According to the percentage of GO, these proteins are classified and displayed in 3 areas: 677 biological processes, 512 cellular components and 1372 molecular functions (fig. 1A).
Currently, general function databases for providing comments are mainly GO, KEGG, COG. Functional annotations are made on the identified proteins using these databases to understand the functional properties of the different proteins. The first 3 most common categories are general functional predictions, shown in FIG. 1B; post-translational modifications, protein turnover, and chaperones; translation, recombination and repair. The KEGG pathway notes for total protein are shown in fig. 1C, with the results showing: many proteins are immune-related. In FIG. 1D, a large number of protein domains are immunoglobulin V-set domains.
4.3 functional Classification and pathway analysis of differentially expressed proteins
PCA principal component analysis showed very significant differences in overall protein reflecting the AF and CAD groups as a whole, with less intra-group variability (FIG. 2). FIG. 3 shows a volcanic plot of these proteins with statistically different up-regulated proteins (. Gtoreq.1.2-fold, P < 0.0.5) in the upper right quadrant. The relative amounts of the different proteins in each sample were then subjected to a cluster analysis, and the situation of the different proteins in the AF group and the CAD group was compared using a cluster heat map (FIG. 4).
Fig. 5A is a classification by biological process, cellular components and molecular function, showing proteins enriched in GO. FIG. 5B shows that the most significantly enriched KEGG pathway is the African trypanosomiasis pathway, and FIG. 5C shows the result of domain enrichment, with the highest degree of enrichment being the immunoglobulin V-set domain.
We then screened 6 secreted proteins with significant differences between AF and CAD groups (table 5).
TABLE 4 patient base case for DIA analysis
TABLE 5DIA analysis of up-regulated secreted proteins in AF group
DIA,data-independent acquisition.
4.4 evaluation of ability of candidate biomarkers to identify AF in tissue Using AUC
ROC analysis was performed and the overall predictive accuracy of the 6 proteins we found in the study as potential biomarkers was assessed by AUC analysis (fig. 6). The AUC values for these proteins were between 0.807 and 0.941. The highest protein with the highest AUC value was P00491 (0.9412, PNP), followed by A0A024R462 (0.9034, FN 1), P02776 (0.8655, PF 4), P08697 (0.8277, SERPINF 2), A0A024R0T9 (0.8067, APOC2), A0A024R930 (0.8067, PRG 4).
4.5 ELISA biomarker validation
To further verify these results, we collected 30 healthy volunteers and 48 atrial fibrillation patients for ELISA verification. Peripheral blood was taken from healthy volunteers and left atrial blood was taken from patients with atrial fibrillation on the day of radio frequency ablation. During the validation process we measured the difference in expression of 6 candidate proteins in both groups (figure 7). Quantitative verification of ELISA method is in good agreement with previous DIA results.
4.6 evaluation of candidate biomarkers in plasma Using AUC to identify AF
ROC analysis was performed and the overall predictive accuracy of 6 proteins as potential biomarkers in peripheral blood and atrial blood plasma was assessed by AUC analysis (fig. 8). Wherein the AUC value of the peripheral blood protein is between 0.5771 and 0.8910, and the AUC value of the 6 secreted proteins of the atrial blood is between 0.7208 and 0.8471.
A variety of cardiac markers have now been found to be useful in cardiovascular disease diagnosis and treatment, such as BNP and cTn, for ABC stroke risk scores (including age, biomarkers, clinical history) in AF patients. The biomarker for searching AF and related complications of AF is beneficial to reducing the risk of the AF patient to generate ischemic stroke and improving prognosis.
The expression profile of secreted proteins in AF plasma is significantly different from that of the control and can be used as AF diagnostic biomarker.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.

Claims (10)

1.A biomarker associated with atrial fibrillation, the biomarker comprising: one or more of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697.
2. Use of a biomarker for the manufacture of a diagnostic product for detecting atrial fibrillation, the biomarker comprising: one or more of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697.
3. The use according to claim 2, wherein the diagnostic product comprises: detection chip, detection reagent or detection kit.
4. The use of claim 2, wherein the biomarker is P00491.
5. The use of claim 2, wherein the biomarkers are P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, and P08697.
6. The use according to claim 2, wherein the test is a test of a subject's peripheral blood, atrial blood or an isolated epicardial adipose tissue sample.
7. The use of claim 6, wherein the detection is a detection of the expression level of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697 protein in the plasma of the subject.
8. The use of claim 7, wherein the biomarker predictive accuracy is assessed by detecting the presence of high expression of the biomarker in the subject, concurrently with ROC curve statistical analysis, and by AUC analysis.
9. The use of claim 8, wherein the biomarker is detected in the plasma of the peripheral blood of the subject with an AUC value of between 0.5771 and 0.8910.
10. The use of claim 8, wherein the biomarker is detected in the plasma of the subject's atrial blood with an AUC value of between 0.7208 and 0.8471.
CN202310904029.1A 2023-07-21 2023-07-21 Biomarker related to atrial fibrillation and application thereof Pending CN116908474A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310904029.1A CN116908474A (en) 2023-07-21 2023-07-21 Biomarker related to atrial fibrillation and application thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310904029.1A CN116908474A (en) 2023-07-21 2023-07-21 Biomarker related to atrial fibrillation and application thereof

Publications (1)

Publication Number Publication Date
CN116908474A true CN116908474A (en) 2023-10-20

Family

ID=88364354

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310904029.1A Pending CN116908474A (en) 2023-07-21 2023-07-21 Biomarker related to atrial fibrillation and application thereof

Country Status (1)

Country Link
CN (1) CN116908474A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117590006A (en) * 2024-01-19 2024-02-23 天津医科大学眼科医院 Application of biomarker in preparation of product for diagnosing Vogt-small Liu Yuantian syndrome

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110234998A (en) * 2016-07-21 2019-09-13 克利夫兰心脏实验室公司 The detection of HDL related protein biomarker group
CN110656169A (en) * 2019-11-05 2020-01-07 天津市人民医院 Diagnostic markers for atrial fibrillation
US20220228144A1 (en) * 2019-08-01 2022-07-21 Alnylam Pharmaceuticals, Inc. SERPIN FAMILY F MEMBER 2 (SERPINF2) iRNA COMPOSITIONS AND METHODS OF USE THEREOF
CN115112776A (en) * 2021-03-18 2022-09-27 中国科学院大连化学物理研究所 Combined marker, application thereof in diagnosis of atrial fibrillation, and diagnostic reagent or kit

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110234998A (en) * 2016-07-21 2019-09-13 克利夫兰心脏实验室公司 The detection of HDL related protein biomarker group
US20220228144A1 (en) * 2019-08-01 2022-07-21 Alnylam Pharmaceuticals, Inc. SERPIN FAMILY F MEMBER 2 (SERPINF2) iRNA COMPOSITIONS AND METHODS OF USE THEREOF
CN110656169A (en) * 2019-11-05 2020-01-07 天津市人民医院 Diagnostic markers for atrial fibrillation
CN115112776A (en) * 2021-03-18 2022-09-27 中国科学院大连化学物理研究所 Combined marker, application thereof in diagnosis of atrial fibrillation, and diagnostic reagent or kit

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
HONGHUANG LIN等: "Whole Blood Gene Expression and Atrial Fibrillation: The Framingham Heart Study", 《PLOS ONE》, pages 2 *
KAZUNOBU等: "Plasma β- Thromboglobulin and Platelet Factor 4 Concentrations in Patients with Atrial fibrillation", 《JAPANESE HEART JOURNAL》 *
MARIYA NEGREVA等: "Early effects of paroxysmal atrial fibrillation on plasma markers of fibrinolysis", 《MEDICINE》 *
MIAO ZHU等: "Identification and verification of FN1, P4HA1 and CREBBP as potential biomarkers in human atrial fibrillation", 《MATHEMATICAL BIOSCIENCES AND ENGINEERING》 *
SHENGJUE XIAO等: "Uncovering potential novel biomarkers and immune infiltration characteristics in persistent atrial fibrillation using integrated bioinformatics analysis", 《MATHEMATICAL BIOSCIENCES AND ENGINEERING》, pages 4707 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117590006A (en) * 2024-01-19 2024-02-23 天津医科大学眼科医院 Application of biomarker in preparation of product for diagnosing Vogt-small Liu Yuantian syndrome
CN117590006B (en) * 2024-01-19 2024-03-29 天津医科大学眼科医院 Application of biomarker in preparation of product for diagnosing Vogt-small Liu Yuantian syndrome

Similar Documents

Publication Publication Date Title
Sigdel et al. Shotgun proteomics identifies proteins specific for acute renal transplant rejection
KR101788414B1 (en) Biomarker for diagnosis of liver cancer and use thereof
Cheng et al. Proteomics analysis for finding serum markers of ovarian cancer
GB2551415A (en) Protein biomarker panels for detecting colorectal cancer and advanced adenoma
US20090069189A1 (en) Method of identifying proteins in human serum indicative of pathologies of human lung tissues
CN116908474A (en) Biomarker related to atrial fibrillation and application thereof
US20050100967A1 (en) Detection of endometrial pathology
Pinet et al. Predicting left ventricular remodeling after a first myocardial infarction by plasma proteome analysis
Song et al. MALDI‐TOF‐MS analysis in low molecular weight serum peptidome biomarkers for NSCLC
He et al. Screening of differentially expressed proteins in placentas from patients with late‐onset preeclampsia
Fu et al. Discovery and verification of urinary peptides in type 2 diabetes mellitus with kidney injury
CN108020669B (en) Application of urinary osteopontin and polypeptide fragment thereof in lung adenocarcinoma
WO2012122094A2 (en) Biomarkers of cardiac ischemia
Horvatovich et al. Biomarker discovery by proteomics: challenges not only for the analytical chemist
CN115436640B (en) Surrogate matrix for polypeptides that can assess the malignancy or probability of thyroid nodules
CN112924692B (en) Diabetes diagnosis kit based on polypeptide quantitative determination and method thereof
CN112924689B (en) Diabetes diagnosis kit based on quantitative determination of polypeptide combined marker and method thereof
Luu et al. Toward improvement of screening through mass spectrometry-based proteomics: ovarian cancer as a case study
Shi et al. Peptidome profiling of human serum of uveal melanoma patients based on magnetic bead fractionation and mass spectrometry
CN113125757A (en) Protein biomarker for early pregnancy diagnosis of sows and method for early pregnancy diagnosis of sows by using protein biomarker
CN112946274A (en) Intracranial aneurysm diagnosis serum marker and serum marker for predicting intracranial aneurysm rupture potential
CN112037852A (en) Method and system for predicting lymph node metastasis of colorectal cancer at stage T1
CN112924690B (en) Serum polypeptide combined marker for early warning and/or diagnosis of diabetes, detection kit and method
Wilz et al. Development of a test to identify bladder cancer in the urine of patients using mass spectroscopy and subcellular localization of the detected proteins
CN116500280B (en) Group of markers for diagnosing carotid aneurysm and application thereof

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination