Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

Prognostic Value of Platelet-Lymphocyte Ratio and High-Density Lipoprotein in Patients with Acute Myocardial Infarct

Acute Myocardial Infarct (AMI) is the main reason for mortality. Platelet to Lymphocyte Ratio (PLR) describesthrombocyte aggregation and inflammation that is linked to cardiovascular disease. High-Density Lipoprotein (HDL) is antiatherogenic.This study aims to analyze the prognostic value of PLR and HDL in patients with AMI. This study was aretrospective observational study by obtaining laboratory results from complete blood count and lipid profiles frominpatients with AMI (STEMI and NSTEMI) medical records during Mei 2019–August 2020. Receiver Operating Characteristics(ROC) analysis was done to get the PLR and HDL cut-off. Prognostic value evaluation was based on sensitivity, specificity,positive and negative predictive value, and accuracy. Results obtained were from 302 subjects with a mean age of 58.4+9.6years old, with most male patients (74.5%). Receiver operating characteristics curve analysis showed an 0.514 Area UnderCurve (AUC) for PLR with p=0.685. High-density lipoprotein ROC was 0.573 with a p=0.033 (p< 0.05), with HDL cut-off = 50.0;sensitivity 72.7%, specificity 32.3%, positive predictive value 63.3%, negative predictive value 42.0% and 57.3% accuracy.Platelet to lymphocyte ratio mean was lower in the HDL <50 group (187.9) compared to the HDL > 50 (210.8), (p=0.009).High-density lipoprotein can be concluded as a potential prognostic factor of acute myocardial infarct. The lower the HDL,the greater the risk for a poor prognosis. A big-scale prospective study should be held to clarify and confirm these findings.

An unruptured “Pocket – Like” giant apical pseudoaneurysm of the left ventricle: A case report

Cardiac pseudoaneurysm is rare and appears mostly as tardive complication of Acute Myocardial Infarct (AMI). Its apical localization is also scarce as it is usually described in posterior or lateral wall of left ventricle. Its diagnosis is based on cardiac imaging. We report a case of a hypertensive, diabetic and smoking 64-year-old man with a past history of anterior AMI. He was symptomatic of chest discomfort. Physical examination indicates an apical murmur, his electrocardiogram showed a regular sinus rhythm and a complete left branch block. The Transthoracic (TTE) echocardiography revealed a giant apical pocketlike aneurysm lined with a clot. Cardiac Magnetic Resonance Imaging (CMRI) confirmed the diagnosis of an apical pseudoaneurysm due to ischemic heart disease in the stage of severe heart failure.

Supervised Analysis for Phenotype Identification: The Case of Heart Failure Ejection Fraction Class

Artificial Intelligence is creating a paradigm shift in health care, with phenotyping patients through clustering techniques being one of the areas of interest. Objective: To develop a predictive model to classify heart failure (HF) patients according to their left ventricular ejection fraction (LVEF), by using available data from Electronic Health Records (EHR). Subjects and methods: 2854 subjects over 25 years old with a diagnosis of HF and LVEF, measured by echocardiography, were selected to develop an algorithm to predict patients with reduced EF using supervised analysis. The performance of the developed algorithm was tested in heart failure patients from Primary Care. To select the most influentual variables, the LASSO algorithm setting was used, and to tackle the issue of one class exceeding the other one by a large amount, we used the Synthetic Minority Oversampling Technique (SMOTE). Finally, Random Forest (RF) and XGBoost models were constructed. Results: The full XGBoost model obtained the maximum accuracy, a high negative predictive value, and the highest positive predictive value. Gender, age, unstable angina, atrial fibrillation and acute myocardial infarct are the variables that most influence EF value. Applied in the EHR dataset, with a total of 25,594 patients with an ICD-code of HF and no regular follow-up in cardiology clinics, 6170 (21.1%) were identified as pertaining to the reduced EF group. Conclusion: The obtained algorithm was able to identify a number of HF patients with reduced ejection fraction, who could benefit from a protocol with a strong possibility of success. Furthermore, the methodology can be used for studies using data extracted from the Electronic Health Records.

Supervised Analysis for Phenotype Identification: The Case of Heart Failure Ejection Fraction Class

Artificial Intelligence are creating a paradigm shift in health care, being phenotyping patients through clustering techniques one of the areas of interest. Objective: To develop a predictive model to classify heart failure (HF) patients according to their left ventricular ejection fraction (LVEF), by using available data in Electronic Health Records (EHR). Subjects and methods: 2854 subjects more than 25 years old with diagnose of HF and LVEF measured by echocardiography were selected to develop an algorithm to predict patients with reduced EF using supervised analysis. Performance of the algorithm developed were tested in heart failure patients from Primary Care. To select the most influencing variables, LASSO algorithm setting was used and to tackle the issue of one class exceed the other one by a large proportion we used the Synthetic Minority Oversampling Technique (SMOTE). Finally, Random Forest (RF) and XGBoost models were constructed. Results: Full XGBoost model obtained the maximized accuracy, a high negative predictive value and the highest positive predictive value. Gender, age, unstable angina, atrial fibrillation and acute myocardial infarct are the variables that most influence FE value. Applied in the EHR data set with a total 25594 patients with an ICD-code of HF and no regular follow-up in Cardiology clinics, 6170 (21.1%) were identified as those pertaining to the reduced EF group. Conclusion: The algorithm obtained is able to rescue a number of HF patients with reduced ejection fraction that can be take benefit for a protocol with strong recommendation to succeed. Furthermore, the methodology can be used for studies with data extracted from the Electronic Health Records.

Intravenous Interferon-β1a for the Treatment of Ischemia-Reperfusion Injury in Acute Myocardial Infarct in Pigs

Background: To investigate the potential of intravenously administered porcine recombinant interferon-β1a (IFN-β1a) for myocardial protection during acute ischemia-reperfusion (IR) injury in an experimental animal model. Methods: Twenty-two piglets (mean ± standard deviation, 26.7 ± 1.65 kg) were assigned to either the IFN group (n = 12) or the control group (n = 10). IR injury was induced by occluding the distal left descending coronary artery for 30 minutes, with a reperfusion period of 6 h. In the IFN group, the animals received 12.5 µg IFN-β1a intravenously repeatedly; the control group received saline solution. The levels of interleukin-6 (IL-6) and cardiac troponin I (TnI) were measured, and the amount of myocardial damage was quantified by analyzing myocardial apoptosis and the mean fluorescence intensity (MFI) of methylene blue–stained cardiac tissue. Results: In the IFN group, significantly more premature deaths occurred compared with the control group (25% versus 17%, P = .013). Between the groups, the mean heart rate was higher in the IFN group (102 ± 22 versus 80 ± 20 beats per minute, P = .02). IL-6 and TnI levels were comparable between the groups, with no significant difference, and there was no difference between the study groups in myocardial apoptosis in the infarcted myocardium. The percentage of MFI differed significantly between the IFN and control groups (90.75% ± 4.90% versus 96.02% ± 2.73%, P = .01). Conclusion: In this acute IR injury animal model, IFN-β1a did not protect the myocardium from IR injury, but rather increased some of the unfavorable outcomes studied.

Upregulated miR-486 Induces Therapeutic Angiogenesis and Improves Infarction Recovery in Rat Myocardial Ischemia Model

BackgroundBesides hematopoietic cells, miR-486 is also enriched in cardiac, skeletal, and smooth muscles. However, its roles in regulating the function of cardiomyocytes and tissue repair in myocardial infarction have not been explored yet.MethodsWe investigated the effects of miR-486 on the survival and hypoxic response of cardiomyocytes. Also, using adenovirus-mediated overexpression, we evaluated its therapeutic effects in myocardial repair in a rat acute myocardial infarct (AMI) model.ResultsHypoxia treatment upregulated miR-486 in cardiomyocytes. Moreover, adenovirus-mediated overexpression of miR-486 reduced cell injury, increased cell viability, and decreased apoptosis in hypoxic conditions. In a rat AMI model, administration of Ad-miR-486 reduced infarct size and collagen deposition, increased vessel density, and improved cardiac function. Furthermore, in vivo data suggest that the protective effects of miR-486 in cardiomyocytes were related to its anti-apoptotic function.ConclusionmiR-486 overexpression protects myocytes from hypoxia-induced apoptosis and has therapeutic potential in myocardial infarction.

Abstract 13306: Impella Combined With Extracorporeal Membrane Oxygenation Synergistically Unloads the Left Ventricle and Reduces Infarct Size in a Model of Myocardial Infarction With Cardiogenic Shock

Introduction: Extracorporeal membrane oxygenation (ECMO) supports hemodynamics in cardiogenic shock (CS) at the expense of left ventricular (LV) overload. LV assist device (LVAD) also supports hemodynamics, whereas LVAD unloads LV. Therefore, the combination of ECMO and LVAD would augment hemodynamic support and unload LV. We hypothesized that the combination therapy in acute myocardial infarct (AMI) in CS could synergistically improve hemodynamics and unload LV, which, in turn, reduces infarct size. Methods: In protocol 1, we ligated coronary arteries and created AMI with CS in 5 mongrel dogs (15.1±0.3 kg). We transvascularly introduced Impella CP into LV. We kept the ECMO flow constant at 1.8L/min. We compared hemodynamics and the LV pressure-volume area (PVA, an index of LV oxygen consumption) under 3 conditions; Control, ECMO, and ECMO+Impella (ECPELLA) in each dog. In protocol 2 (n=15), we ligated coronary arteries for 180 min and then reperfused. We activated Impella CP and/or ECMO from 60 min after the coronary ligation to the end of the experiment. We allocated dogs into 3 groups, no support (Control), ECMO, and ECPELLA and compared infarct size at 180 min after reperfusion among 3 groups. Results: In protocol 1, both ECMO and ECPELLA increased arterial pressure compared to Control (Control: 63±9, ECMO: 88±10 and ECPELLA: 97±18 mmHg, p < 0.05), and resolved the CS status. ECPELLA strikingly reduced PVA by 83% relative to Control (1500±326, 2038±357 and 258±182 mmHg*ml, p<0.001). In protocol 2, ECPELLA markedly reduced the infarct size (15±8%) compared to Control (53±7%, p<0.05) and ECMO (39±10%, p<0.05). Conclusions: ECPELLA before reperfusion markedly improved hemodynamics, reduced PVA, and limited infarct size in a dog model of MI with CS. ECPELLA could prevent ECMO-induced LV overload and synergistically exert powerful anti-infarct effects in AMI with CS.

Abstract 16827: miR-34a Expression in Cardiac Neonatal Mesenchymal Stem Cells is Essential for Heart Regeneration

Advancing chronological age negatively impacts the functional activity of stem cell-based therapies. Despite the early promise stem cell mediated differentiation into selected cellular lineages when injected in the chosen organ, stem cell’s functional unit is the secretome that is directly modulated by chronological aging. However, the precise mechanism driving the secretome potency is unknown. Here we show a single miRNA, influenced by aging, drives the potency of the stem cell secretome at multiple cellular levels by increasing exosome production and directly increasing the levels of independent stem cell paracrine factors. We show differential miRNA microarray analysis of cardiac neonatal mesenchymal stem cells (nMSCs) and adult MSCs (aMSCs) identified miR34a among the top ten differentially expressed miRNAs present in aMSCs but not nMSCs. We demonstrated that miR34a singly inhibits the aMSC’s regenerative abilities in the acute myocardial infarct model by decreasing the secretome potency when compared to nMSCs in knockdown studies of miR-34a. Moreover, overexpression of miR-34a in nMSCs reversed the strong regenerative properties of nMSCs by decreasing their secretome potency. Mechanistically, miR-34a regulates the secretome potency firstly by decreasing Heat Shock Factor 1 (HSF1) levels that directly decreases exosome production and alters the exosome cargo to a less-regenerative phenotype, and secondly by directly inhibiting transcriptional levels of critical stem cell paracrine factors. These results implicate the miR34a-HIF1 pathway as a critical pathway controlling the secretome of MSCs impacted by advancing chronological age. Our findings further advance miRNA-based therapeutic approaches to cardiac repair and heart regeneration by indicating how to improve the quality of secretome of transplanted stem cells.

The importance of clinically relevant background therapy in cardioprotective studies

Treatment of acute myocardial infarct patients (AMI) includes rapid restoration of coronary blood flow and pharmacological therapy aimed to prevent pain and maintain vessel patency. Many interventions have been investigated to offer additional protection. One such intervention is remote ischaemic conditioning (RIC) involving short-episodes of ischaemia of the arm with a blood pressure cuff, followed by reperfusion to protect the heart organs from subsequent severe ischaemia. However, the recent CONDI2-ERIC-PPCI multicentre study of RIC in STEMI showed no benefit in clinical outcome in low risk patients. It could also be argued that these patients were already in a partially protected state, highlighting the disconnect between animal- and clinical-based outcome studies. To improve potential translatability, we developed an animal model using pharmacological agents similar to those given to patients presenting with an AMI, prior to PPCI. Rats underwent MI on a combined background of an opioid agonist, heparin and a platelet-inhibitor thereby allowing us to assess whether additional cardioprotective strategies had any effect over and above this “cocktail”. We demonstrated that the “background drugs” were protective in their own right, reducing MI from 57.5 ± 3.7% to 37.3 ± 2.9% (n = 11, p < 0.001). On this background of drugs, RIC did not add any further protection (38.0 ± 3.4%). However, using a caspase inhibitor, which acts via a different mechanistic pathway to RIC, we were able to demonstrate additional protection (20.6 ± 3.3%). This concept provides initial evidence to develop models which can be used to evaluate future animal-to-clinical translation in cardioprotective studies.