Myocardial Injury Is Distinguished from Stable Angina by a Set of Candidate Plasma Biomarkers Identified Using iTRAQ/MRM-Based Approach

Multi-Omics Research on Angina Pectoris: A Novel Perspective

Angina pectoris (AP), a clinical syndrome characterized by paroxysmal chest pain, is caused by insufficient blood supply to the coronary arteries and sudden temporary myocardial ischemia and hypoxia. Long-term AP typically induces other cardiovascular events, including myocardial infarction and heart failure, posing a serious threat to patient safety. However, AP's complex pathological mechanisms and developmental processes introduce significant challenges in the rapid diagnosis and accurate treatment of its different subtypes, including stable angina pectoris (SAP), unstable angina pectoris (UAP), and variant angina pectoris (VAP). Omics research has contributed significantly to revealing the pathological mechanisms of various diseases with the rapid development of high-throughput sequencing approaches. The application of multi-omics approaches effectively interprets systematic information on diseases from the perspective of genes, RNAs, proteins, and metabolites. Integrating multi-omics research introduces novel avenues for identifying biomarkers to distinguish different AP subtypes. This study reviewed articles related to multi-omics and AP to elaborate on the research progress in multi-omics approaches (including genomics, transcriptomics, proteomics, and metabolomics), summarized their applications in screening biomarkers employed to discriminate multiple AP subtypes, and delineated integration methods for multi-omics approaches. Finally, we discussed the advantages and disadvantages of applying a single-omics approach in distinguishing diverse AP subtypes. Our review demonstrated that the integration of multi-omics technologies is preferable for quick and precise diagnosis of the three AP types, namely SAP, UAP, and VAP.

α1-Antichymotrypsin Complex (SERPINA3) Is an Independent Predictor of All-Cause but Not Cardiovascular Mortality in Patients Hospitalized for Chest Pain of Suspected Coronary Origin

INTRODUCTION

SERPINA3 is an acute-phase protein triggered by inflammation. It is upregulated after an acute myocardial infarction (AMI). Data on its long-term prognostic value in MI patients are scarce. We aimed to assess the utility of SERPINA3 as a prognostic marker in patients hospitalized for chest pain of suspected coronary origin.

METHODS

A total of 871 consecutive patients, 386 diagnosed with AMI, were included. Stepwise Cox regression models, applying continuous loge-transformed values, were fitted for the biomarker with all-cause mortality and cardiac death within 2 years or all-cause mortality within the median 7 years as dependent variables. An analysis of MI and stroke, and combined endpoints, respectively, was added. The hazard ratio (HR) (95% CI) was assessed in a univariate and multivariable model.

RESULTS

Plasma samples from 847 patients were available. By 2-year follow-up, 138 (15.8%) patients had died, of which 86 were cardiac deaths. The univariate analysis showed a significant association between SERPINA3 and all-cause mortality (HR 1.41 [95% 1.19-1.68], p < 0.001) but not for cardiac death. Associations after adjustment were non-significant. By 7-year follow-up, 332 (38.1%) patients had died. SERPINA3 was independently associated with all-cause mortality from the third year onward. The HR was 1.14 (95% CI, 1.02-1.28), p = 0.022. Similar results applied to combined endpoints, but not for MI and stroke, respectively. The prognostic value of SERPINA3 was limited to non-AMI patients. No independent associations were noted among AMI patients.

CONCLUSIONS

SERPINA3 predicts long-term all-cause mortality but fails to predict outcome in AMI patients.

Insight into the underlying molecular mechanism of dilated cardiomyopathy through integrative analysis of data mining, iTRAQ-PRM proteomics and bioinformatics

BACKGROUND

DCM is a common cardiomyopathy worldwide, which is characterized by ventricular dilatation and systolic dysfunction. DCM is one of the most widespread diseases contributing to sudden death and heart failure. However, our understanding of its molecular mechanisms is limited because of its etiology and underlying mechanisms. Hence, this study explored the underlying molecular mechanism of dilated cardiomyopathy through integrative analysis of data mining, iTRAQ-PRM proteomics and bioinformatics METHODS: DCM target genes were downloaded from the public databases. Next, DCM was induced in 20 rats by 8 weeks doxorubicin treatment (2.5 mg/kg/week). We applied isobaric tags for a relative and absolute quantification (iTRAQ) coupled with proteomics approach to identify differentially expressed proteins (DEPs) in myocardial tissue. After association analysis of the DEPs and the key target genes, subsequent analyses, including functional annotation, pathway enrichment, validation, were performed.

RESULTS

Nine hundred thirty-five genes were identified as key target genes from public databases. Meanwhile, a total of 782 DEPs, including 348 up-regulated and 434 down-regulated proteins, were identified in our animal experiment. The functional annotation of these DEPs revealed complicated molecular mechanisms including TCA cycle, Oxidative phosphorylation, Cardiac muscle contraction. Moreover, the DEPs were analyzed for association with the key target genes screened in the public dataset. We further determined the importance of these three pathways.

CONCLUSION

Our results demonstrate that TCA cycle, Oxidative phosphorylation, Cardiac muscle contraction played important roles in the detailed molecular mechanisms of DCM.

The Search for Associations of Serum Proteins with the Presence of Unstable Atherosclerotic Plaque in Coronary Atherosclerosis

To study the associations of blood proteins with the presence of unstable atherosclerotic plaques in the arteries of patients with coronary atherosclerosis using quantitative proteomics. The studies involved two groups of men with coronary atherosclerosis (group 1 (St) had only stable atherosclerotic plaques; group 2 (Ns) had only unstable atherosclerotic plaques, according to histological analysis of tissue samples); the average age of patients was 57.95 ± 7.22. Protein concentrations in serum samples were determined using the PeptiQuant Plus Proteomics Kit. The identification of protein fractions was carried out by monitoring multiple reactions on a Q-TRAP 6500 mass spectrometer combined with a liquid chromatograph. Mass spectrometric identification revealed in serum samples from patients with unstable atherosclerotic plaques a reduced concentration of proteins in the blood: α-1-acid glycoprotein, α-1-antichymotrypsin, α-1-antitrypsin, ceruloplasmin, hemopexin, haptoglobin, apolipoprotein B-100, apolipoprotein L1, afamin and complement component (C3, C7, C9). Moreover, at the same time a high concentration complements factor H and attractin. The differences were considered significant at p < 0.05. It was found that the instability of atherosclerotic plaques is associated with the concentration of proteins: afamin, attractin, components of the complement system, hemopexin and haptoglobin. The data of our study showed the association of some blood proteins with the instability of atherosclerotic plaques in coronary atherosclerosis. Their potential role in the development of this disease and the possibility of using the studied proteins as biomarkers requires further research.

UPLC-HDMSE to discover serum biomarkers in adults with type 1 diabetes

Type 1 diabetes (T1D) is a complex disease with metabolic and functional changes that can alter an individual's proteome. An LC-MS/MS analytical method, in an HDMS^E system, was used to identify differentially expressed proteins in the high abundance protein-depleted serum of T1D patients and healthy controls. Samples were processed in Progenesis QI for Proteomics software. A functional enrichment of the proteins was performed with Gene Ontology and ToppGene, and the interactions were visualized by STRING 11.5. As a result, 139 proteins were identified, 14 of which were downregulated in the serum of patients with T1D compared to controls. Most of the differentially expressed proteins were shown to be involved with the immune system, inflammation, and growth hormone stimulus response, and were associated with the progression of T1D. Differential protein expression data showed for the first-time changes in CPN2 expression levels in the serum of patients with T1D. Our findings indicate that these proteins are targets of interest for future investigations and for validation of protein biomarkers in T1D.

The Association and Pathogenesis of SERPINA3 in Coronary Artery Disease

Background: Serine proteinase inhibitor A3 (SERPINA3) has been discovered in the pathogenesis of many human diseases, but little is known about the role of SERPINA3 in coronary artery disease (CAD). Therefore, we aim to determine its relationship with CAD and its function in the pathogenesis of atherosclerosis.

Methods: In total 86 patients with CAD and 64 patients with non-CAD were compared. The plasma SERPINA3 levels were measured using ELISA. Logistic regression analysis and receiver-operating characteristic (ROC) analysis were performed to illustrate the association between plasma SERPINA3 levels and CAD. In vitro, real-time PCR (RT-PCR) and immunofluorescence staining were used to determine the expression of SERPINA3 in atherosclerotic plaques and their component cells. Then rat aortic smooth muscle cells (RASMCs) were transfected with siRNA to knock down the expression of SERPINA3 and human umbilical vein endothelial cells (HUVECs) were stimulated by SERPINA3 protein. EdU assay and scratch assay were used for assessing the capability of proliferation and migration. The cell signaling pathway was evaluated by western blot and RT-PCR.

Results: Patients with CAD [104.4(54.5–259.2) μg/mL] had higher levels of plasma SERPINA3 than non-CAD [65.3(47.5–137.3) μg/mL] (P = 0.004). After being fully adjusted, both log-transformed and tertiles of plasma SERPINA3 levels were significantly associated with CAD. While its diagnostic value was relatively low since the area under the ROC curve was 0.64 (95% CI: 0.55–0.73). Secreted SERPINA3 might increase the expression of inflammatory factors in HUVECs. Vascular smooth muscle cells had the highest SERPINA3 expression among the aorta compared to endothelial cells and inflammatory cells. The knockdown of SERPINA3 in RASMCs attenuated its proliferation and migration. The phosphorylated IκBα and its downstream pathway were inhibited when SERPINA3 was knocked down.

Conclusions: Elevated plasma SERPINA3 levels were associated with CAD. SERPINA3 can increase inflammatory factors expression in HUVECs. It can regulate VSMCs proliferation, migration, and releasing of inflammatory factors through the NF-κB signaling pathway. Thus, SERPINA3 played a significant role in the pathogenesis of atherosclerosis.

Application of an Exploratory Knowledge-Discovery Pipeline Based on Machine Learning to Multi-Scale OMICS Data to Characterise Myocardial Injury in a Cohort of Patients with Septic Shock: An Observational Study

Currently, there is no therapy targeting septic cardiomyopathy (SC), a key contributor to organ dysfunction in sepsis. In this study, we used a machine learning (ML) pipeline to explore transcriptomic, proteomic, and metabolomic data from patients with septic shock, and prospectively collected measurements of high-sensitive cardiac troponin and echocardiography. The purposes of the study were to suggest an exploratory methodology to identify and characterise the multiOMICs profile of (i) myocardial injury in patients with septic shock, and of (ii) cardiac dysfunction in patients with myocardial injury. The study included 27 adult patients admitted for septic shock. Peripheral blood samples for OMICS analysis and measurements of high-sensitive cardiac troponin T (hscTnT) were collected at two time points during the ICU stay. A ML-based study was designed and implemented to untangle the relations among the OMICS domains and the aforesaid biomarkers. The resulting ML pipeline consisted of two main experimental phases: recursive feature selection (FS) assessing the stability of biomarkers, and classification to characterise the multiOMICS profile of the target biomarkers. The application of a ML pipeline to circulate OMICS data in patients with septic shock has the potential to predict the risk of myocardial injury and the risk of cardiac dysfunction.

Pathological cardiac remodeling seen by the eyes of proteomics

Cardiac remodeling involves cellular and structural changes that occur as consequence of multifactorial events to maintain the homeostasis. The progression of pathological cardiac remodeling involves a transition from adaptive to maladaptive changes that eventually leads to impairment of ventricular function and heart failure. In this scenario, proteins are key elements that orchestrate molecular events as increased expression of fetal genes, neurohormonal and second messengers' activation, contractile dysfunction, rearrangement of the extracellular matrix and alterations in heart geometry. Mass spectrometry based-proteomics has emerged as a sound method to study protein dysregulation and identification of cardiac diseases biomarkers in plasma. In this review, we summarize the main findings related to large-scale proteome modulation of cardiac cells and extracellular matrix occurred during pathological cardiac remodeling. We describe the recent proteomic progresses in the selection of protein targets and introduce the renin-angiotensin system as an interesting target for the treatment of pathological cardiac remodeling.

iTRAQ and PRM-based quantitative proteomics in early recurrent spontaneous abortion: biomarkers discovery

Background

Early recurrent spontaneous abortion (ERSA) is a common condition in pregnant women. To prevent ERSA is necessary to look for abortion indicators, such as hormones and proteins, in an early stage.

Methods

Thirty patients with ERSA were enrolled in the case group. In the control group, we recruited 30 healthy women without a history of miscarriage undergoing voluntary pregnancy termination. The differentially expressed proteins in the serum were identified between the two groups using PRM and iTRAQ.

Results

Seventy-eight differentially expressed proteins were identified. Using GO functional annotation and KEGG pathway analysis, we detected that the most significant changes occurred in the pathway of Fc gamma R-mediated phagocytosis. Meanwhile, using PRM, we identified three proteins that were closely related to abortion, B4DTF1 (highly similar to PSG1), P11464 (PSG1), and B4DF70 (highly similar to Prdx-2). The levels of B4DTF1 and P11464 were down-regulated, while the level of B4DF70 was up-regulated.

Conclusions

CD45, PSG1, and Prdx-2, were significantly dysregulated in the samples of ERSA and could become important biomarkers for the prediction and diagnosis of ERSA. Larger‑scale studies are required to confirm the diagnostic value of these biomarkers.

Applications of multiple reaction monitoring targeted proteomics assays in human plasma

Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation. Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the keywords: 'MRM/SRM plasma proteomic/proteomics/proteome'. The retrieved studies were further filtered to focus on disease biomarkers and the main results are summarized. Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labeled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.

Quantitative proteomic analysis of human corneal epithelial cells infected with HSV-1

HSV-1 infection in corneal epithelium initiates the process of herpes simplex keratitis. We investigated the dynamic change of the host proteins in corneal epithelial cells infected with HSV-1 to understand the virus-host interaction. iTRAQ coupled with LC-MS/MS was applied to quantitatively analyze the protein profiles in HSV-1 infected corneal epithelial cells at 6 and 24 h post-infection (hpi), and the results were validated by multiple reaction monitoring (MRM). We also performed bioinformatic analysis to investigate the potentially important signal pathways and protein interaction networks in the host response to HSV-1 infection. We identified 292 proteins were up-regulated and 168 proteins were down-regulated at 6 hpi, while 132 proteins were up-regulated and 89 proteins were down-regulated at 24 hpi, which were validated by MRM analysis. We found the most enriched GO terms were translational initiation, cytosol, poly(A) RNA binding, mRNA splicing via spliceosome and extracellular exosome for the dysregulated proteins. KEGG pathway analysis revealed significant changes in metabolism pathway characterized by decreased tricarboxylic acid cycle activity and increased glycolysis. Proteins interaction network analysis indicated several proteins including P4HB, ACLY, HSP90AA1 and EIF4A3, might be critical proteins in the host-virus response. Our study for the first time analyzed the protein profile of HSV-1 infected primary corneal epithelial cells by quantitative proteomics. These findings help to better understand the host-virus interaction and the pathogenesis of herpes simplex keratitis.

Integrated Proteomics and Metabolomic Analyses of Plasma Injury Biomarkers in a Serious Brain Trauma Model in Rats

Diffuse axonal injury (DAI) is a prevalent and serious brain injury with significant morbidity and disability. However, the underlying pathogenesis of DAI remains largely unclear, and there are still no objective laboratory-based tests available for clinicians to make an early diagnosis of DAI. An integrated analysis of metabolomic data and proteomic data may be useful to identify all of the molecular mechanisms of DAI and novel potential biomarkers. Therefore, we established a rat model of DAI, and applied an integrated UPLC-Q-TOF/MS-based metabolomics and isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis to obtain unbiased profiling data. Differential analysis identified 34 metabolites and 43 proteins in rat plasma of the injury group. Two metabolites (acetone and 4-Hydroxybenzaldehyde) and two proteins (Alpha-1-antiproteinase and Alpha-1-acid glycoprotein) were identified as potential biomarkers for DAI, and all may play important roles in the pathogenesis of DAI. Our study demonstrated the feasibility of integrated metabolomics and proteomics method to uncover the underlying molecular mechanisms of DAI, and may help provide clinicians with some novel diagnostic biomarkers and therapeutic targets.

Proteomics and multivariate modelling reveal sex-specific alterations in distinct regions of human carotid atheroma

Background

Atherosclerotic lesions are comprised of distinct regions with different proteomic profiles. Men and women develop differences in lesion phenotype, with lesions from women generally being more stable and less prone to rupture. We aimed to investigate the differences in proteomic profiles between sexes, including distinct lesion regions, to identify altered proteins that contribute to these differences observed clinically.

Methods

Carotid endarterectomy samples (ten men/ten women) were obtained, and intraplaque biopsies from three distinct regions (internal control, fatty streak and plaque) were analysed by tandem-mass spectrometry. Multivariate statistical modelling, using orthogonal partial least square-discriminant analysis, was used to discriminate the proteomes between men and women.

Results

Multivariate discriminant modelling revealed proteins from 16 functional groups that displayed sex-specific associations. Additional statistics revealed ten proteins that display region-specific alterations when comparing sexes, including proteins related to inflammatory response, response to reactive oxygen species, complement activation, transport and blood coagulation. Transport protein afamin and blood coagulation proteins antithrombin-III and coagulation factor XII were significantly increased in plaque region from women. Inflammatory response proteins lysozyme C and phospholipase A2 membrane-associated were significantly increased in plaque region from men. Limitations with this study are the small sample size, limited patient information and lack of complementary histology to control for cell type differences between sexes.

Conclusions

This pilot study, for the first time, utilises a multivariate proteomic approach to investigate sexual dimorphism in human atherosclerotic tissue, and provides an essential proteomic platform for further investigations to help understand sexual dimorphism and plaque vulnerability in atherosclerosis.

Electronic supplementary material

The online version of this article (10.1186/s13293-018-0217-3) contains supplementary material, which is available to authorized users.

Screening and Identification of Pregnancy Zone Protein and Leucine-Rich Alpha-2-Glycoprotein as Potential Serum Biomarkers for Early-Onset Myocardial Infarction using Protein Profile Analysis

PURPOSE

The present study aims to discover novel serum biomarkers of early-onset myocardial infarction (MI) using proteomic analysis.

EXPERIMENTAL DESIGN

In the first stage, the iTRAQ-coupled LC-MS/MS technique is utilized to investigate protein profiles of patients with early-onset MI. In the second stage, these candidate proteins are validated using ELISA.

RESULTS

A total of 538 proteins are quantified, with pregnancy zone protein (PZP), leucine-rich α-2-glycoprotein (LRG) and Apolipoprotein C-I (Apo C-I) being upregulated and Apolipoprotein A-I (Apo A-I) and Apolipoprotein A-IV (Apo A-IV) downregulated in early-onset MI patients. Results from the validation stage demonstrate that the serum concentrations of PZP and LRG are significantly increased in the early-onset MI group. The correlation between the concentrations of C-reactive protein (CRP) and the two candidate biomarkers is positive. Area under the curve values used to diagnose early-onset MI for LRG and PZP are 0.939 and 0.874, respectively.

CONCLUSIONS AND CLINICAL RELEVANCE

Five differential serum proteins are identified in early-onset MI using proteomic analysis. Lipoprotein-related biomarkers further demonstrate the close relationship between lipid metabolism and the disease. Inflammation-associated LRG and PZP may be novel biomarkers of the disease. In addition, changes in these proteins may partly reveal the possible mechanisms in the pathogenesis and pathophysiology of early-onset MI.

Identification of plasma biomarkers for diffuse axonal injury in rats by iTRAQ-coupled LC-MS/MS and bioinformatics analysis

DAI is a serious and complex brain injury associated with significant morbidity and mortality. The lack of reliable objective diagnostic modalities for DAI delays administration of therapeutic interventions. Hence, identifying reliable biomarkers is urgently needed to enable early DAI diagnosis in the clinic. Herein, we established a rat model of DAI and applied an isobaric tags for a relative and absolute quantification (iTRAQ) coupled with nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS) proteomics approach to screen differentially expressed plasma proteins associated with DAI. A total of 58 proteins were found to be significantly modulated in blood plasma samples of the injury group in at least one time point compared to controls. Bioinformatics analysis of the differentially expressed proteins revealed that the pathogenesis of axonal injury underlying DAI is multi-stage biological process involved. Two significantly changed proteins, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and hemopexin (Hpx), were identified as potential diagnostic biomarkers for DAI, and were successfully confirmed by further western blot analysis. This proteomic profiling study not only identified novel plasma biomarkers that may facilitate the development of clinically diagnostic for DAI, but also provided enhanced understanding of the molecular mechanisms underlying DAI.