CN116908474B

CN116908474B - Biomarker related to atrial fibrillation and application thereof

Info

Publication number: CN116908474B
Application number: CN202310904029.1A
Authority: CN
Inventors: 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
Original assignee: Beijing Chaoyang Hospital
Current assignee: Beijing Chaoyang Hospital
Priority date: 2023-07-21
Filing date: 2023-07-21
Publication date: 2024-05-17
Anticipated expiration: 2043-07-21
Also published as: CN116908474A

Abstract

The invention 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 invention 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 invention 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 invention 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 invention to provide biomarkers related to atrial fibrillation that can be used as biomarkers for atrial fibrillation detection.

A second object of the present invention 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 invention, 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 invention, 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 invention 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 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 expression level of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697 protein in epicardial adipose tissue in 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 lower 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 lower 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 lower than 0.8277;

The biomarker is P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697, and the AUC value is not lower than 0.987 when combined.

Preferably, the assay is an assay for detecting the expression level of P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, P08697 protein 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 lower 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 lower 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 lower than 0.6847;

The biomarker is P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930, and P08697, and 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 lower 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 lower 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 lower than 0.7177;

The biomarker is P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697, and the AUC is not lower than 0.904 when combined.

The beneficial effects are that:

The P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697 proteins provided by the invention 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 invention 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 invention, 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 invention 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 invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Examples

1. Experimental major reagent and manufacturer name

IRT kit 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 a national drug group (cat number 10023218); mass spectrum grade pancreatin was purchased from Promega company (cat No. V5280); ammonium bicarbonate was purchased from Sigma (cat number 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 (cat No. 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. No. 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, left at room temperature for 5min, and 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

Protein samples were taken, added to DB protein lysate (8M urea, 100mM TEAB, pH=8.5) to make up to 100. Mu.L, pancreatin and 100mM TEAB buffer were added, mixed well, digested for 4h at 37℃and then digested overnight with pancreatin and CaCl ₂. 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. Each fraction was collected by taking 4. Mu.g of the supernatant, adding 0.8. Mu.l of iRT reagent, and then taking half of the volume of each sample and performing machine detection. The UHPLC system was upgraded with EASY-nLC ^TM nm, 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 were as shown in Table 2. Using Q Exactive ^TM series mass spectrometer, nanospray Flex ^TM (ESI) ion source, setting ion spray voltage to 2.1kV, ion transmission tube temperature to 320 ℃, adopting Data Dependent Acquisition (DDA) mode for mass spectrum, setting mass spectrum full scanning range to m/z 350-1500, setting primary mass spectrum resolution to 120000 (200 m/z), C-trap maximum capacity to 3×10 ⁶, and C-trap maximum injection time to 80ms; the method comprises the steps of selecting parent ions with ion intensity TOP 40 in full scanning, carrying out secondary mass spectrum detection by using a high-energy collision fragmentation (HCD) method, setting the resolution of the secondary mass spectrum to 15000 (200 m/z), setting the maximum capacity of C-trap to 5X 10 ⁴, setting the maximum injection time of C-trap to 45ms, setting the fragmentation collision energy of peptide fragments to 27%, setting the threshold intensity to 1.1X 10 ⁴, setting the dynamic exclusion range to 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 taken for each sample, 0.8. Mu.l of iRT reagent was added, and then half of the volume of each sample was taken for machine detection. The UHPLC system was upgraded with EASY-nLC ^TM nm, the pre-column was a self-prepared pre-column (4.5 cm. Times.75 μm,3 μm) and the analytical column was a 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 Exactive ^TM series mass spectrometer, nanospray Flex ^TM (ESI) ion source, setting ion spray voltage to 2.1kV, ion transmission tube temperature to 320 ℃, adopting non-data dependent acquisition mode (DIA) for mass spectrum, setting mass spectrum full scanning range to be m/z 350-1500, setting primary mass spectrum resolution to 60000 (200 m/z), setting C-trap maximum capacity to 5×10 ⁵, and setting C-trap maximum injection time to 20ms; the secondary mass spectrum detection was performed using HCD method fragmentation, the resolution of the secondary mass spectrum was set to 30000 (200 m/z), the maximum capacity of C-trap was 1X10 ⁶, and the fragmentation collision energy of the peptide fragment was set to 27%, yielding the raw data (. Raw.) for mass spectrum detection.

2.6 Data analysis

2.6.1 Identification and quantification of proteins

Machine data in DDA scan mode was searched for using search software Proteome Discoverer 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% 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% are removed.

Importing Spectronaut version 14.0.0 Biognosys software into PD2.2 software library searching identification results to generate a spectrum chart library; setting peptide fragments and ion pair selection rules; selecting peptide fragments and sub-ions meeting the conditions from the spectrogram to generate TARGET LIST; DIA data is imported, ion pair chromatographic peaks are extracted according to 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 interproscan 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. The inclusion criteria are ① history of atrial-free fibrillation; ② Atrial fibrillation history cardiovascular disease ③ had 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 an 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, the general function databases for providing comments mainly include 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 DIA patient base analyzed

TABLE 5 DIA analysis of up-regulated secreted proteins in AF groups

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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 protein with the highest AUC value is P00491 (0.9412, PNP), followed by A0A024R462(0.9034,FN1),P02776(0.8655,PF4),P08697(0.8277,SERPINF2),A0A024R0T9(0.8067,APOC2),A0A024R930(0.8067,PRG4).

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 invention, and not for limiting the same; although the invention 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 invention.

Claims

1. Use of a biomarker for the manufacture of a diagnostic product for detecting atrial fibrillation, the biomarker comprising: p00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, and P08697;

The detection refers to detection of peripheral blood, atrial blood or an isolated epicardial adipose tissue sample of a subject; performing ROC curve statistical analysis simultaneously by detecting the presence of high expression of the biomarker in the subject, and assessing biomarker predictive accuracy by AUC analysis;

Detecting a biomarker in the isolated epicardial adipose tissue of the subject, wherein the biomarker is P00491, A0a024R462, P02776, A0a024R0T9, A0a024R930, and P08697, and the AUC value is not less than 0.987 when the biomarker is combined;

The biomarker in the blood plasma of the peripheral blood of a subject is detected by taking an AUC value as a standard for diagnosing atrial fibrillation, wherein the AUC value is not lower than 0.934 when P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697 are combined;

The biomarker in the blood plasma of the atrial blood of the subject is detected by taking the AUC value as a standard for diagnosing atrial fibrillation, wherein the AUC value is not lower than 0.904 when P00491, A0A024R462, P02776, A0A024R0T9, A0A024R930 and P08697 are combined.

2. The use according to claim 1, wherein the diagnostic product comprises: detection chip, detection reagent or detection kit.