Proteomic Evaluation of the Thrombosis-inflammation Interplay in STEMI with MVO

doi:10.21203/rs.3.rs-4716191/v1

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Research Article

Proteomic Evaluation of the Thrombosis-inflammation Interplay in STEMI with MVO

https://doi.org/10.21203/rs.3.rs-4716191/v1

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Background

Coronary microvascular obstruction (MVO) occurs in up to half of acute myocardial infarction patients receiving successful primary percutaneous coronary intervention (pPCI) and is associated with a much worse outcome. Whereas the fluid phase cross-talk between thrombosis and inflammation is well appreciated, the pathophysiological implication is still scant.

Objectives

This study sought to investigate the differentially expressed proteins and possible biological processes involved in MVO after pPCI in ST-segment elevation myocardial infarction (STEMI) patients based on thrombus proteomics.

Methods

Aspirated thrombi and pPCI from 16 STEMI patients within 12 h of symptom onset were collected, including 8 MI with MVO (MVO+) and 8 MI without MVO (MVO-). 4D label-free proteomics was used to explore the differentially expressed proteins. Gene ontology enrichment analysis was performed using Metascape software and protein‒protein interaction analysis was performed using Cystoscope software. Afterward, the Connectivity Map database was used to select drug candidates for MVO treatment.

Results

We identified a total of 471 proteins with expression changes greater than 1.5-fold at P < 0.05, of which 50 were significantly upregulated and 421 were downregulated in the MVO + group compared with the MVO- group. Gene ontology enrichment analysis of significant differentially expressed proteins revealed the central role of platelet activation and neutrophil degranulation processes in patients with MVO. The protein‒protein interaction network also confirmed the significant interaction of inflammation and platelet activation, which may mediate the role of thrombus-inflammation in the pathogenesis of MVO. Drug screening revealed 4 drug candidates for MVO treatment: D-64131, TC-1, SB-431542 and alvespimycin.

Conclusions

Using the thrombus proteomic approach, we revealed the central role of the thrombus-inflammation interaction and potential drug candidates in STEMI with MVO. The findings from our study will contribute to the treatment of MVO in the future.

STEMI

CMR

microvascular obstruction

thrombus‒inflammation

proteomics

Acute ST-segment elevated myocardial infarction (STEMI) accounts for the leading cause and mortality of cardiovascular disease (CVD) worldwide, making it a major health-care challenge[1]. Acute luminal thrombosis in the coronary artery is one of the main causes of STEMI [2]. Emergency primary percutaneous coronary intervention (pPCI) is the preferred reperfusion strategy to restore the patency of the infarct-related artery, thereby limiting the irreversible damage of ischemia, reducing the reperfusion injury, and rescuing the survived myocardium[3, 4, 5]. In fact, revascularization of epicardial vessels does not equal myocardial reperfusion at the microvascular level, and 5–50% of patients still develop coronary microcirculation obstruction (MVO, microvessel diameter < 200 micron) after successful recanalization of criminal vessels[6, 7]. MVO, which manifests clinically as coronary no-reflow in the infarct-related artery, is one of the important factors determining the final infarct size of the heart and the poor prognosis[8]. Therefore, it is very important to explore the early pathogenesis mechanism of MVO and find new effective treatment approaches.

Studies have shown that the inflammatory storm caused by ischemic/reperfusion (I/R) injury is one of the important mechanisms leading to MVO formation[9]. The characteristics of the thrombus-inflammation paradigm deem STEMI as a result of a systemic proinflammatory state, which leads to endothelial dysfunction, coronary microvascular dysfunction, abnormal cardiac structure and function, and death[10]. However, the evidence supporting the relationship between the characteristics of thrombi and inflammation is primarily based on animal studies and investigating a single or limited number of proteins. Because proteins are the functional executors of the cell, an in-depth characterization of the proteome and signal transduction of thrombi will lay a foundation for comprehensively understanding the molecular mechanisms of STEMI with MVO. High‒throughput proteomic technologies enable the investigation of a large set of proteins in a single sample [11]. The resultant biomarker profiles are potentially useful for characterizing underlying pathophysiological pathways and lead to earlier and more accurate detection of cardiovascular syndromes.

In this study, we conducted 4D label-free proteomic profiles of thrombi from 16 STEMI patients with or without MVO. Our research aimed to (1) provide a comprehensive profile of differentially expressed proteins among STEMI patients with and without MVO and (2) explore potential drugs to treat MVO.

Ethics statement

This study was approved by the Nanjing Drum Ethics Committee (Ethics Number: 2021-531-01), and complied with the Declaration of Helsinki. All participants gave written informed consent.

Study design

We collected coronary thrombus tissue samples from STEMI patients receiving thrombus aspiration from January 2020 to October 2021 at the Department of Cardiology of Nanjing Drum Tower Hospital. The STEMI patients met the diagnostic criteria as outlined by the 2019 European Society of Cardiology (ESC) guidelines. The inclusion criteria were as follows: 1) age ranging from 18 to 80 years old; 2) admission within 12 hours of chest pain onset; 3) a STEMI diagnosis; and 4) subjecting to thrombus aspiration. Exclusion criteria the following: 1) current infections; 2) previous history of myocardial infarction or stroke, malignant tumors, severe liver and kidney dysfunction and rheumatic immune-related conditions; and 3) withdrawn from the study over the course of treatment.

MVO is diagnosed as: 1) lack of gadolinium uptake on first pass perfusion; 2) lack of early gadolinium enhancement; and 3) lack of late gadolinium enhancement (LGE) (10–15 min after contrast administration)[12]. The groups were defined as STEMI with or without microvascular obstruction (MVO + and MVO-) (Fig. 2B).

Sample collection

According to the protocol, all patients were pretreated with aspirin and clopidogrel. Unfractioned heparin adjusted to body weight was used during examination in the catheterization laboratory. Aspirated blood and intracoronary thrombus material were collected in a collection bottle with a filter. The aspirated thrombus material was divided into three portions: one was embedded in OCT (Sakura, USA) for pathology, one was stored in glutaraldehyde for electron microscopy imaging, and the other was frozen at -80°C for proteomic analysis. Approximately 3 ml of coronary blood was collected in a tube containing EDTA and centrifuged at 3000 rpm for 20 min at 4℃. The supernatant containing plasma was collected and stored at -80℃ until analysis.

Protein Extraction

Thrombus samples (n = 8 each group) were prepared for 4D label-free proteomics analysis. A total of 10–50 mg of each sample was ground in liquid nitrogen into a cell powder and then disrupted in 4-fold volumes of lysis buffer (8 M urea, 1% protease inhibitor cocktail), sonicated three times on ice (high intensity ultrasonic processor, Scientz), and centrifuged at 12000 × g for 10 min at 4°C. The supernatant was collected and measured with the BCA method. A total of 20 µg of protein extract from the thrombus was loaded in 10% SDS‒PAG.

4D Label-free Proteomics

Tandem mass spectrometry (MS/MS) analysis was performed using an EASY-nLC 1000 ultraperformance liquid chromatography (UPLC) system with buffer A (0.1% formic acid and 2% acetonitrile) and B (0.1% formic acid and 100% acetonitrile) coupled to a Q Executive Plus Orbitrap mass spectrometer at a resolution of 17,500 via an EASY-Spray nanoelectrospray ionization source (Thermo Fisher, USA). Peptide (0.5 µg) was injected into the column, and the gradient was used to perform separation at a flow rate of 450 nL/min: 6–24% B (0–70 min), 24–35% B (70–84 min), 35–80% B (84–87 min), and 80% B (87–90 min). MS/MS data analysis was conducted via the MaxQuant search engine (1.6.15.0). Tandem mass spectra were searched against the human UniProt database concatenated with a reverse decoy database. The peptide false-discovery rate (FDR) was ≤ 1%.

Bioinformatics analysis of quantifiable proteins

Data generated were compared by using Student’s test for two group comparisons. Proteins with a fold change ≥ 1.5 and a P value < 0.05 were considered significantly differentially expressed proteins. For functional enrichment of the identified proteins, Metascape was used to map proteins into the Gene Ontology (GO terms) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Protein‒protein interaction (PPI) network analysis was performed using the STRING database and visualized using Cytoscape.

Screening of Potential Drug Molecules

Connectivity MAP is a database of the association between drug bioactive small molecules and gene expression. This study utilized the Connectivity Map website (https://broadinstitute.org/CMap) to predict small molecule compounds that target MVO. Subsequently, 50 upregulated proteins were entered into the website for drug screening. The prediction score represented the correlation between the drug and DEGs, and a negative correlation indicated that the drug was suitable for the treatment of MVO. In this study, − 60 was selected as the threshold of the prediction score to screen drug candidates for MVO treatment.

Scanning electron microscopy (SEM).

Thrombi were fixed in 2.5% glutaraldehyde for 1 h, rinsed in saline and fixed in 1% osmium tetroxide for 1 h. Then samples were dehydrated in a graded series of ethyl alcohol solutions. Dehydrated specimens were critical-point dried, mounted on studs and sputter coated before SEM imaging.

Histology.

Thrombi were embedded in OCT and serially cut at a thickness of 5 µm. Samples were stained with hematoxylin and eosin (HE) and imaged (10X and 40X magnification). Immunohistochemical analysis was performed with antibodies against CD11b (granulocytes) and CD61 (platelets). After blocking nonspecific reactions with 10% donkey serum and 2% Triton X-100, the sections were incubated with primary antibodies at 4°C overnight. The next day, secondary antibody conjugated with HRP/DAB was used for 1 hour.

Statistical analysis.

For the statistical analysis of the clinical characteristics of STEMI patients with versus without MVO, a t test was used for continuous variables, and a chi-squared test or Fisher’s exact test was used for categorical variables. Data were statistically analyzed using GraphPad Prism 8.4.0 software, and a p value less than 0.05 was indicative of statistical significance.

STEMI patients with MVO demonstrated worse cardiac function

A schematic of the experimental design is shown in Fig. 1. The present study collected a total of 16 thrombi samples from STEMI patients with thrombosis aspiration. Patient characteristics in this study are described in Table 1. Both MI (with MVO and without MVO) groups were matched for age, sex and BMI (all P > 0.05). Compared with the MVO - group, the MVO + group showed poorer cardiac function (EF, P = 0.0041) and higher inflammatory markers (CRP, P = 0.0216). This suggested that the poor cardiac function in MVO patients was partially related to the inflammatory response.

Table 1

Baseline clinical characteristics between STEMI patients with or without MVO.
Characteristic	MVO – (n = 30)	MVO + (n = 18)	P value
Demographics
Age, yrs	57.23 ± 12.81	60.50 ± 12.31	0.3900
Men, %	28(93.33)	16(88.89)	0.6244
BMI, kg/m²	24.27 ± 3.11	24.35 ± 3.24	0.9505
Systolic BP, mmHg	119.7 ± 19.69	117.4 ± 18.52	0.7006
Diastolic BP, mmHg	73.97 ± 17.13	71.00 ± 7.837	0.4933
Smoking history, %	14(46.67)	7(38.89)	0.5990
Prior conditions
Angina pectoris, %	11 (36.67)	5 (27.78)	0.5271
Hypertension, %	16(53.33)	12(66.67)	0.3643
Diabetes mellitus, %	4(13.33)	4(22.22)	0.6892
Stroke, %	3 (10.00)	3 (16.67)	0.8217
Clinical characteristics
Time from symptoms onset to admission ≤ 12 h, %	24 (80.00)	13 (72.22)	0.5348
Killip class ≥ 2, %	4(13.33)	3(16.67)	0.9159
Medications
Aspirin, %	30	18	-
Antiplatelet, %	30	18	-
Unfractionated heparin, %	30	18	-
Laboratory values
Fasting glucose, mmol/L	7.06 ± 3.10	7.26 ± 2.30	0.8125
Triglycerides, mmol/L	1.96 ± 1.77	1.59 ± 1.18	0.4273
Total cholesterol, mmol/L	4.29 ± 1.07	4.05 ± 0.81	0.4208
HDL-C, mmol/L	0.96 ± 0.26	1.07 ± 0.34	0.2203
LDL-C, mmol/L	2.43 ± 0.83	2.27 ± 0.69	0.4962
TnT, µg/L	4.75 ± 3.25	5.90 ± 3.80	0.3369
Leukocyte count, 10*9/L	10.77 ± 3.55	11.98 ± 4.13	0.2877
Neutrophil count, 10*9/L	8.32 ± 3.06	9.71 ± 3.70	0.1669
Monocyte count, 10*9/L	0.73 ± 0.39	0.74 ± 0.44	0.9640
Erythrocyte count, 10*12/L	4.52 ± 0.49	4.21 ± 0.66	0.0711
Neutrophile/RBC	1.83 ± 0.61	2.32 ± 0.84	0.0266
Platelet count, 10*9/L	201.7 ± 77.82	209.8 ± 76.61	0.7260
Hemoglobin, g/L	144.4 ± 15.22	133.6 ± 19.35	0.0377
CRP, mg/L	12.71 13.58	31.28 ± 39.95	0.0216
Infarct-related arteries			0.1793
LAD, %	12(40)	12(67)
LCX, %	5(17)	1(5)
RCA, %	13(43)	5(28)
Ejection fraction, %	51.03 ± 10.32	40.03 ± 14.87	0.0041

Thrombotic tissue from MVO patients shows increased neutrophil infiltration and decreased fibrin content

We observed thrombi aspirated from STEMI patients without or with MVO under the macroscopic view (Fig. 2A-B). Transmission electron microscopy (TEM) revealed that patients with MVO exhibited a weaker fibrin network structure and increased infiltration of granulocytes in thrombus tissue compared to patients without MVO (Fig. 2C). Hematoxylin and eosin (H&E) staining results showed that thrombus tissues in MVO + patients had increased granulocyte infiltration and less fibrin compared to those in MVO- patients (Fig. 2D). MOVAT staining showed that compared to patients without MVO, patients with MVO had fewer fibrinogen components in thrombus tissue. Immunohistochemistry showed that compared to patients without MVO, patients with MVO had more severe granulocyte infiltration and increased platelet recruitment in the thrombus tissue (Fig. 2F-G). Hence, these findings indicated that the instability of thrombosis and the inflammatory response are associated with poor microvascular perfusion, leading to adverse cardiac remodeling and worse clinical outcomes.

Differentially expressed proteins in thrombotic tissues from STEMI patients with or without MVO

To further investigate the mechanism of thrombosis formation in STEMI patients with or without MVO, after appropriate sample quality control and normalization procedures, a total of 2538 quantified proteins were identified in both groups using 4D liquid chromatography-tandem mass spectrometry (LC‒MS/MS)-based label-free quantification proteomics. There were 471 proteins with expression changes greater than 1.5-fold at P < 0.05 between the MI with MVO and MI without MVO groups, including 50 upregulated proteins and 421 downregulated proteins in the MVO group (Fig. 3). The top 5 upregulated proteins included CYP20A1, IL6ST, DSG1, COL4A1 and TNS1, while the top 5 downregulated proteins included CA13, COX6C, EFR3A, RNF11 and TEX2. The upregulation and downregulation of specific proteins suggest a complex interaction between various biological pathways that contribute to the development and progression of microvascular obstruction (MVO). Understanding these protein expression changes could lead to the identification of potential therapeutic targets to mitigate the adverse effects associated with MVO.

Inflammatory response participates in the pathogenesis of thrombosis in MVO patients

We further used Metascape (https://Metascape.org) to explore the functional enrichment of upregulated proteins. As shown in Fig. 4, the enriched terms included O2/CO2 exchange in erythrocytes, neutrophil degranulation, platelet activation, complement and coagulation cascades and acute inflammatory response. The functional enrichment results suggested that coagulation and inflammation processes were involved in the pathogenesis of MVO. These findings provided insights into the molecular mechanisms underlying MVO and highlighted potential therapeutic targets for intervention.

SLC4A1 and SLC2A1 were involved in thrombosis formation in STEMI patients with MVO

To explore the interaction of upregulated proteins, we constructed a PPI network using Cytoscape. As shown in Fig. 5, significant interactions were observed. We had identified the core roles of SLC4A1 and SLC2A1 in thrombosis formation in MVO patients, both of which are involved in coagulation and inflammatory responses. Understanding these interactions provides a deeper insight into the molecular mechanisms driving thrombus instability and inflammation in MVO, potentially guiding future therapeutic interventions.

Screening potential therapeutic drugs for MVO

50 upregulated genes in the MVO group were uploaded to Connectivity MAP, and then the scores of drug candidates that could be used for MVO treatment were obtained. A total of 4 drug candidates were screened out with scores < − 60 (Table 2), including the tubulin inhibitor D-64131, beta secretase inhibitor TC-1, TGF-beta receptor inhibitor SB-431542, and HSP inhibitor alvespimycin. These drug candidates highlight potential therapeutic avenues for mitigating the adverse effects associated with MVO, targeting key pathways involved in thrombus formation and inflammation.

Table 2

Predicted drug candidates based on connectivity MAP analysis.
Rank	Compound	MOA	Score	SMILES
1	D-64131	Tubulin inhibitor	-62.58	COC1 = CC2 = C(C = C1)NC(= C2)C(= O)C3 = CC = CC = C3
2	TC-1	Beta secretase inhibitor	-62.45	C1C2C3C4C1C5C2C6C3C4C5(N6CCC7 = CC(= CC = C7)F)O
3	SB-431542	TGF-beta receptor inhibitor	-62.34	C1OC2 = C(O1)C = C(C = C2)C3 = C(NC(= N3)C4 = CC = C(C = C4)C(= O)N)C5 = CC = CC = N5
4	alvespimycin	HSP inhibitor	-61.47	C[C@H]1C[C@@H]([C@@H]([C@H](/C = C(/[C@@H]([C@H](/C = C\C = C(\C(= O)NC2 = CC(= O)C(= C(C1)C2 = O)NCCN(C)C)/C)OC)OC(= O)N)\C)C)O)OC
MOA, mechanism of action.

In the proteomic investigation of the association of thrombus and inflammation, we identified 50 upregulated proteins and 421 downregulated proteins in the MVO group. The upregulated proteins were significantly enriched in O2/CO2 exchange in erythrocytes, neutrophil degranulation, platelet activation, complement and coagulation cascades and acute inflammatory response. Protein‒protein interaction analysis revealed the central role of SLC4A1 and SLC2A1, which are both involved in the coagulation and inflammation response. Moreover, drug screening discovered 4 drug candidates for MVO treatment: D-64131, TC-1, SB-431542 and alvespimycin. Our study was the first to evaluate inflammation comprehensively in STEMI with MVO using high throughput proteomics, and confirmed the role of inflammation as a mediator between thrombosis and MVO.

Thrombosis-inflammation paradigm in STEMI

In STEMI patients with high thrombus burden, thrombectomy during primary PCI did not further reduce CV death, MI, cardiogenic shock, or Class IV heart failure compared with PCI alone, but did significantly increase stroke [13, 14]. Additionally, antithrombotic regimens cannot completely prevent thrombotic events [15, 16]. In contrast, the highly dynamic and orchestrated inflammatory response is rapidly mounted to the injured area, which, paradoxically, can further exacerbate myocardial injury [17, 18]. This implies that a therapeutic gap due to a third, not yet adequately addressed mechanism, inflammation, has received considerable attention owing to the coronavirus disease COVID-19 pandemic [19, 20]. Therefore, an emerging concept is of particular interest to target thromboinflammation—that is, the aberrant and excessive activation of immunothrombosis—contributes to preventing thrombotic complications in CVD [10]. From Table 1, the statistics of baseline clinical characteristics, we found that the CRP value, a downstream marker of IL-6, and the ratio of neutrophils/RBCs were higher in the MVO + group than in the MVO- group, although the number of inflammatory cells in circulation was comparable, which indicated that the degree of polarization of inflammatory cells and the pathophysiology mechanisms in the microenvironment of thrombosis may vary in the two groups.

SLC4A1 and SLC2A1 may be mediators between inflammation and thrombosis

Previous studies have suggested that MVO by cardiac magnetic resonance imaging (CMR) is a major contributor to final infarct size and provides independent prognostic value [21]. Mechanistically, microvascular dysfunction is primarily caused by endothelial swelling, coronary microembolization of atherosclerotic debris, cardiomyocyte swelling, vasomotion dysfunction, aggregation of leukocytes, platelets and erythrocytes, and capillary destruction and hemorrhage [9, 22]. Therefore, we hypothesize that some factors relating to immune thrombosis are directly or indirectly involved in MVO formation. From the 4D high-throughput proteomics data of coronary thrombi, we identified that the enriched terms included neutrophil degranulation, platelet activation, complement and coagulation cascades, acute inflammatory response, and O2/CO2 exchange in erythrocytes. The functional enrichment results strongly suggested that coagulation and inflammation processes were involved in the pathogenesis of MVO.

In addition, protein‒protein interaction analysis revealed the central role of SLC4A1 and SLC2A1. The SLC4A1 gene located on chromosome 17q21-q22 encodes two proteins: the longer erythrocyte SLC4A1 protein and the shorter kidney SLC4A1 protein. It is a transmembrane glycoprotein involved in anion exchange as Na+-independent CI-/HCO3-exchanges [23]. It is widely expressed in erythrocytes, kidney, heart and colon [24]. SLC4A1 has been previously reported to be related to thromboembolism disease and diabetes mellitus [25, 26]. In addition, SLC4A1 was also associated with inflammation [5] and oxidative stress [24]. However, the effect of SLC4A1 in myocardial infarction has not been reported. Solute carrier family 2 member 1 (SLC2A1, also known as glucose transporter 1 (GLUT1)) is the major inducible glucose transporter for glucose uptake to fuel the glycolytic pathway and works in almost all mammalian cells, especially in activated leukocytes [27]. Neutrophils are the first leukocytes to massively invade the myocardium after AMI, and their inflammatory function relies greatly on glycolysis [28]. In response to immunological stimulation, neutrophil increase the surface expression of SLC2A1 for glucose uptake, as an energy source for neutrophil extracellular trap (NET) formation [29, 30]. Moreover, glucose metabolism transformation allows for NADPH production, thereby fueling NADPH oxidase to produce superoxide and NET release [31]. Collectively, inhibition of SLC4A1, SLC2A1 or both may attenuate the formation and release of NETs, alleviating reperfusion injury and MVO formation.

Clinical impact and future research.

Traditional risk assessment tools are only modestly prognostic in people with known cardiovascular disease, or elderly individuals without confirmed cardiovascular disease [32]. The insensitivity to improvements in traditional risk factors and imaging measurements is a problem for both clinical trials and medical practice [33]. Individualizing residual cardiovascular risk assessment enables precisive allocation and monitoring of the benefit of cardioprotective therapies [34]. Inflammation biomarkers may have potential in screening, diagnostic, and prognostic purposes for STEMI with MVO [35, 36]. Several inflammation-related proteins in our study deserve further investigation, either a biomarker for screening or as potential therapeutic targets in preclinical practice. Furthermore, we screened potential therapeutic drugs for treating MVO. Considering that increased systemic inflammation is a precursor of STEMI and the progression of recovery, which is supported by our results, it would be worthwhile to investigate whether early modulation of inflammatory blood cells prevents or delays the onset of cardiovascular frailty.

Limitations.

Our study does have some limitations. It is important to note that these results were obtained with aspirated material obtained during PCI, and it is unclear to what extent anticoagulant drug therapies applied prior to angioplasty could modify the thrombus proteome. On the other hand, thrombus aspiration according to the Class 2B guidelines, as our cohort was from a single research center, its relatively low number of enrolled patients might potentially introduce selection bias and residual confounding. The differentially expressed proteins need to be further validated in a larger cohort of patients. Finally, to determine the prognostic value of the identified biomarkers, the patient follow-up data should be further considered for the occurrence of major adverse cardiovascular events.

Overall, we identified 50 upregulated proteins and 421 downregulated proteins in the MVO group. These proteins were significantly enriched in neutrophil degranulation and platelet activation, suggesting an interaction of thrombosis-inflammation. Our study provides new proof-of-concept of the proteomics characteristics of STEMI patients with MVO.

CMR, cardiac magnetic resonance imaging

CVD, cardiovascular disease

GO, Gene Ontology

MVO, microvascular obstruction

pPCI, primary percutaneous coronary intervention

SEM, scanning electron microscopy

STEMI, ST-segment elevation myocardial infarction

Author contributions

Yu Qi: Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Visualization. Yufang Li: Formal analysis, Investigation, Data Curation, Writing - Original Draft, Visualization. Xuan Wei: Software, Validation, Formal analysis, Data Curation, Writing - Original Draft. Han Wu: Investigation, Data Curation. Guannan Li: Investigation, Data Curation. Jianzhou Chen: Software, Validation, Writing - Review & Editing. Lina Kang: Resources, Funding acquisition, Writing - Review & Editing, Project administration. Kun Wang: Conceptualization, Funding acquisition, Writing - Review & Editing, Project administration. All authors reviewed the manuscript.

Conflicts of interest

The authors declare no competing interests.

Acknowledgments

The authors thank PTM BIO company (Hangzhou, Zhejiang Province, China) for its assistance with mass spectrometry analysis.

Declaration of Generative AI and AI-assisted technologies in the writing process

AI-assisted technology was not used in the preparation of this work (except checking grammar and spelling).

Availability of data and material

All supporting data are available within the online supplementary files or from the corresponding author upon reasonable request. An expanded methods section is included in the Data Supplement.

Funding

This research was supported by Key Project supported by Medical Science and technology development Foundation, Nanjing Department of Health. (No. ZKX23011 to Kun Wang) and the Nanjing Medical Science and Technical Development Foundation (No. ZKX20018 to Lina Kang).

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Proteomic Evaluation of the Thrombosis-inflammation Interplay in STEMI with MVO

Status:

Version 1

Abstract

Background

Objectives

Methods

Results

Conclusions

Figures

Introduction

Material and Methods

Ethics statement

Study design

Sample collection

Protein Extraction

4D Label-free Proteomics

Bioinformatics analysis of quantifiable proteins

Screening of Potential Drug Molecules

Statistical analysis.

Results

STEMI patients with MVO demonstrated worse cardiac function

Thrombotic tissue from MVO patients shows increased neutrophil infiltration and decreased fibrin content

Differentially expressed proteins in thrombotic tissues from STEMI patients with or without MVO

Inflammatory response participates in the pathogenesis of thrombosis in MVO patients

SLC4A1 and SLC2A1 were involved in thrombosis formation in STEMI patients with MVO

Screening potential therapeutic drugs for MVO

Discussion

Thrombosis-inflammation paradigm in STEMI

SLC4A1 and SLC2A1 may be mediators between inflammation and thrombosis

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1