HCG18, LEF1AS1 and lncCEACAM21 as biomarkers of disease severity in the peripheral blood mononuclear cells of COVID-19 patients.

BACKGROUND: Even after 3 years from SARS-CoV-2 identification, COVID-19 is still a persistent and dangerous global infectious disease. Significant improvements in our understanding of the disease pathophysiology have now been achieved. Nonetheless, reliable and accurate biomarkers for the early stratification of COVID-19 severity are still lacking. Long noncoding RNAs (LncRNAs) are ncRNAs longer than 200 nucleotides, regulating the transcription and translation of protein-coding genes and they can be found in the peripheral blood, thus holding a promising biomarker potential. Specifically, peripheral blood mononuclear cells (PBMCs) have emerged as a source of indirect biomarkers mirroring the conditions of tissues: they include monocytes, B and T lymphocytes, and natural killer T cells (NKT), being highly informative for immune-related events. METHODS: We profiled by RNA-Sequencing a panel of 2906 lncRNAs to investigate their modulation in PBMCs of a pilot group of COVID-19 patients, followed by qPCR validation in 111 hospitalized COVID-19 patients. RESULTS: The levels of four lncRNAs were found to be decreased in association with COVID-19 mortality and disease severity: HLA Complex Group 18-242 and -244 (HCG18-242 and HCG18-244), Lymphoid Enhancer Binding Factor 1-antisense 1 (LEF1-AS1) and lncCEACAM21 (i.e. ENST00000601116.5, a lncRNA in the CEACAM21 locus). Interestingly, these deregulations were confirmed in an independent patient group of hospitalized patients and by the re-analysis of publicly available single-cell transcriptome datasets. The identified lncRNAs were expressed in all of the PBMC cell types and inversely correlated with the neutrophil/lymphocyte ratio (NLR), an inflammatory marker. In vitro, the expression of LEF1-AS1 and lncCEACAM21 was decreased upon THP-1 monocytes exposure to a relevant stimulus, hypoxia. CONCLUSION: The identified COVID-19-lncRNAs are proposed as potential innovative biomarkers of COVID-19 severity and mortality.

GATA3 as a Blood-Based RNA Biomarker for Idiopathic Parkinson's Disease.

Finding novel biomarkers for Parkinson's disease (PD) is crucial for early disease diagnosis, severity assessment and identifying novel disease-modifying drug targets. Our study aimed at investigating the GATA3 mRNA levels in whole blood samples of idiopathic PD (iPD) patients with different disease severities as a biomarker for iPD. The present study is a cross-sectional, case-control study, with samples obtained from the Luxembourg Parkinson's cohort (LuxPARK). iPD (N = 319) patients, along with age-matched controls without PD (non-PD; N = 319) were included in this study. Blood GATA3 mRNA expression was measured using quantitative reverse transcription PCR (RT-qPCR) assays. The capacity of GATA3 expression levels to establish the diagnosis of iPD (primary end-point) and assess disease severity (secondary end-point) was determined. The blood levels of GATA3 were significantly lower in iPD patients, compared to non-PD controls (p ≤ 0.001). Logistic regression models showed a significant association of GATA3 expression with iPD diagnosis after adjustment for the confounders (p = 0.005). Moreover, the addition of GATA3 expression to a baseline clinical model improved its iPD diagnosis capacity (p = 0.005). There was a significant association of GATA3 expression levels with the overall disease severity (p = 0.002), non-motor experiences of daily living (nm-EDL; p = 0.003) and sleep disturbances (p = 0.01). Our results suggest that GATA3 expression measured in blood may serve as a novel biomarker and may help in the diagnosis of iPD and assessment of disease severity.

Association of miR-21-5p, miR-122-5p, and miR-320a-3p with 90-Day Mortality in Cardiogenic Shock.

Cardiogenic shock (CS) is a life-threatening emergency. New biomarkers are needed in order to detect patients at greater risk of adverse outcome. Our aim was to assess the characteristics of miR-21-5p, miR-122-5p, and miR-320a-3p in CS and evaluate the value of their expression levels in risk prediction. Circulating levels of miR-21-5p, miR-122-5p, and miR-320a-3p were measured from serial plasma samples of 179 patients during the first 5-10 days after detection of CS, derived from the CardShock study. Acute coronary syndrome was the most common cause (80%) of CS. Baseline (0 h) levels of miR-21-5p, miR-122-5p, and miR-320a-3p were all significantly elevated in nonsurvivors compared to survivors (p < 0.05 for all). Above median levels at 0h of each miRNA were each significantly associated with higher lactate and alanine aminotransferase levels and decreased glomerular filtration rates. After adjusting the multivariate regression analysis with established CS risk factors, miR-21-5p and miR-320a-3p levels above median at 0 h were independently associated with 90-day all-cause mortality (adjusted hazard ratio 1.8 (95% confidence interval 1.1-3.0), p = 0.018; adjusted hazard ratio 1.9 (95% confidence interval 1.2-3.2), p = 0.009, respectively). In conclusion, circulating plasma levels of miR-21-5p, miR-122-5p, and miR-320a-3p at baseline were all elevated in nonsurvivors of CS and associated with markers of hypoperfusion. Above median levels of miR-21-5p and miR-320a-3p at baseline appear to independently predict 90-day all-cause mortality. This indicates the potential of miRNAs as biomarkers for risk assessment in cardiogenic shock.

A heart-enriched antisense long non-coding RNA regulates the balance between cardiac and skeletal muscle triadin.

Non-coding RNAs play major roles in cardiac pathophysiology. Recent studies reported that long non-coding RNAs (lncRNAs) are dysregulated in the failing heart, but how they contribute to heart failure development is unclear. In this study, we aimed to identify heart-enriched lncRNAs and investigate their regulation and function in the failing heart. RESULTS: Analysis of a RNA-seq dataset of 15 Caucasian tissues allowed the identification of 415 heart-enriched lncRNAs. Fifty-three lncRNAs were located on the genome in close vicinity to protein-coding genes associated with cardiac function and disease. Analysis of a second RNA-seq dataset of 16 failing human hearts highlighted one lncRNA which we arbitrarily named TRDN-AS due to its localisation in the antisense position of the gene encoding triadin (TRDN). Expression of TRDN-AS and cardiac TRDN was up-regulated in biopsies from failing human hearts compared to control hearts. In failing hearts, TRDN-AS was positively correlated with a cardiac isoform of TRDN and negatively correlated with a skeletal muscle isoform of TRDN. A murine homolog of human TRDN-AS was identified and found to be enriched in the heart and localised in the nuclear compartment of cardiomyocytes. Trdn-AS expression as well as the ratio between cardiac and skeletal muscle isoforms were down-regulated after experimental myocardial infarction. In murine cardiomyocytes, activation of Trdn-AS transcription with the CRISPR/dCas9-VPR system enhanced the ratio between cardiac and skeletal isoforms of Trdn. CONCLUSION: The lncRNA TRDN-AS regulates the balance between cardiac and skeletal isoforms of triadin. This finding may have implications for the treatment of heart failure.

Long noncoding RNAs in patients with acute myocardial infarction.

RATIONALE: Long noncoding RNAs (lncRNAs) constitute a novel class of noncoding RNAs that regulate gene expression. Although recent data suggest that lncRNAs may be associated with cardiac disease, little is known about lncRNAs in the setting of myocardial ischemia. OBJECTIVE: To measure lncRNAs in patients with myocardial infarction (MI). METHODS AND RESULTS: We enrolled 414 patients with acute MI treated by primary percutaneous coronary intervention. Blood samples were harvested at the time of reperfusion. Expression levels of 5 lncRNAs were measured in peripheral blood cells by quantitative polymerase chain reaction: hypoxia inducible factor 1A antisense RNA 2, cyclin-dependent kinase inhibitor 2B antisense RNA 1 (ANRIL), potassium voltage-gated channel, KQT-like subfamily, member 1 opposite strand/antisense transcript 1 (KCNQ1OT1), myocardial infarction-associated transcript, and metastasis-associated lung adenocarcinoma transcript 1. Levels of hypoxia inducible factor 1A antisense RNA 2, KCNQ1OT1, and metastasis-associated lung adenocarcinoma transcript 1 were higher in patients with MI than in healthy volunteers (P<0.01), and levels of ANRIL were lower in patients with MI (P=0.003). Patients with ST-segment-elevation MI had lower levels of ANRIL (P<0.001), KCNQ1OT1 (P<0.001), myocardial infarction-associated transcript (P<0.001), and metastasis-associated lung adenocarcinoma transcript 1 (P=0.005) when compared with patients with non-ST-segment-elevation MI. Levels of ANRIL were associated with age, diabetes mellitus, and hypertension. Patients presenting within 3 hours of chest pain onset had elevated levels of hypoxia inducible factor 1A antisense RNA 2 when compared with patients presenting later on. ANRIL, KCNQ1OT1, myocardial infarction-associated transcript, and metastasis-associated lung adenocarcinoma transcript 1 were significant univariable predictors of left ventricular dysfunction as assessed by an ejection fraction ≤40% at 4-month follow-up. In multivariable and reclassification analyses, ANRIL and KCNQ1OT1 improved the prediction of left ventricular dysfunction by a model, including demographic features, clinical parameters, and cardiac biomarkers. CONCLUSIONS: Levels of lncRNAs in blood cells are regulated after MI and may help in prediction of outcome. This motivates further investigation of the role of lncRNAs after MI.

Identification of candidate long non-coding RNAs in response to myocardial infarction.

BACKGROUND: Long non-coding RNAs (lncRNAs) constitute a novel class of non-coding RNAs. LncRNAs regulate gene expression, thus having the possibility to modulate disease progression. In this study, we investigated the changes of lncRNAs expression in the heart after myocardial infarction (MI). RESULTS: Adult male C57/BL6 mice were subjected to coronary ligation or sham operation. In a derivation group of 4 MI and 4 sham-operated mice sacrificed 24 hours after surgery, microarray analysis showed that MI was associated with up-regulation of 20 lncRNAs and down-regulation of 10 lncRNAs (fold-change >2). Among these, 2 lncRNAs, called myocardial infarction-associated transcript 1 (MIRT1) and 2 (MIRT2), showed robust up-regulation in the MI group: 5-fold and 13-fold, respectively. Up-regulation of these 2 lncRNAs after MI was confirmed by quantitative PCR in an independent validation group of 8 MI and 8 sham-operated mice (9-fold and 16-fold for MIRT1 and MIRT2, P < 0.001). In a time-course analysis involving 21 additional MI mice, the expression of both lncRNAs peaked 24 hours after MI and returned to baseline after 2 days. In situ hybridization revealed an up-regulation of MIRT1 expression in the left ventricle of MI mice. Expression of MIRT1 and MIRT2 correlated with the expression of multiple genes known to be involved in left ventricular remodeling. Mice with high level of expression of MIRT1 and MIRT2 had a preserved ejection fraction. CONCLUSION: Myocardial infarction induces important changes in the expression of lncRNAs in the heart. This study motivates further investigation of the role of lncRNAs in left ventricular remodeling.

A Machine Learning Model Based on microRNAs for the Diagnosis of Essential Hypertension.

INTRODUCTION: Hypertension is a major and modifiable risk factor for cardiovascular diseases. Essential, primary, or idiopathic hypertension accounts for 90-95% of all cases. Identifying novel biomarkers specific to essential hypertension may help in understanding pathophysiological pathways and developing personalized treatments. We tested whether the integration of circulating microRNAs (miRNAs) and clinical risk factors via machine learning modeling may provide useful information and novel tools for essential hypertension diagnosis and management. MATERIALS AND METHODS: In total, 174 participants were enrolled in the present observational case-control study, among which, there were 89 patients with essential hypertension and 85 controls. A discovery phase was conducted using small RNA sequencing in whole blood samples obtained from age- and sex-matched hypertension patients (n = 30) and controls (n = 30). A validation phase using RT-qPCR involved the remaining 114 participants. For machine learning, 170 participants with complete data were used to generate and evaluate the classification model. RESULTS: Small RNA sequencing identified seven miRNAs downregulated in hypertensive patients as compared with controls in the discovery group, of which six were confirmed with RT-qPCR. In the validation group, miR-210-3p/361-3p/362-5p/378a-5p/501-5p were also downregulated in hypertensive patients. A machine learning support vector machine (SVM) model including clinical risk factors (sex, BMI, alcohol use, current smoker, and hypertension family history), miR-361-3p, and miR-501-5p was able to classify hypertension patients in a test dataset with an AUC of 0.90, a balanced accuracy of 0.87, a sensitivity of 0.83, and a specificity of 0.91. While five miRNAs exhibited substantial downregulation in hypertension patients, only miR-361-3p and miR-501-5p, alongside clinical risk factors, were consistently chosen in at least eight out of ten sub-training sets within the SVM model. CONCLUSIONS: This study highlights the potential significance of miRNA-based biomarkers in deepening our understanding of hypertension's pathophysiology and in personalizing treatment strategies. The strong performance of the SVM model highlights its potential as a valuable asset for diagnosing and managing essential hypertension. The model remains to be extensively validated in independent patient cohorts before evaluating its added value in a clinical setting.

Circulating microRNAs after cardiac arrest.

OBJECTIVE: Prediction of clinical outcome after cardiac arrest is clinically important. While the potential of circulating microRNAs as biomarkers of acute coronary syndromes is an active field of investigation, it is unknown whether microRNAs are associated with outcome in cardiac arrest patients. DESIGN: Prospective, single-center proof-of-concept study. SETTING: Eighteen-bed adult general intensive care unit of an academic tertiary care hospital in Luxembourg. PATIENTS: Twenty-eight patients with cardiac arrest treated by therapeutic hypothermia after cardiac resuscitation were enrolled. MEASUREMENTS AND MAIN RESULTS: Blood samples were obtained at 48 hrs after cardiac arrest for the determination of microRNA levels and neuron-specific enolase. Neurological outcome was determined by the cerebral performance category at discharge from the intensive care unit and at 6-month follow-up. Analysis of microRNA arrays and quantitative assessment by polymerase chain reaction identified two microRNAs, miR-122 and miR-21, overexpressed in patients with poor neurological outcome (cerebral performance category 3-5, n = 14) compared to patients with favorable neurological outcome (cerebral performance category 1-2, n = 14) (48-fold and three-fold, respectively). In vitro experiments showed that both miR-122 and miR-21 are produced by neuronal cells, indicating that the elevation of circulating levels of these microRNAs after cardiac arrest may reflect brain damage. miR-122 and miR-21 predicted neurological outcome with areas under the receiver operating characteristic curve of 0.73 and 0.77, respectively. Patients within the highest third of miR-122 or miR-21 values had elevated mortality rate (p = .02). Neuron-specific enolase was an accurate predictor of neurological outcome (areas under the receiver operating characteristic curve = 0.98) and mortality (p < .001). MicroRNA levels were not associated with myocardial damage or activation of inflammation. CONCLUSIONS: As compared to neuron-specific enolase, circulating microRNAs are modest but significant predictors of neurological outcome and mortality in this small group of patients with cardiac arrest. This motivates assessing the prognostic value of microRNAs in larger cohorts of cardiac arrest patients.

Use of circulating microRNAs to diagnose acute myocardial infarction.

BACKGROUND: Rapid and correct diagnosis of acute myocardial infarction (MI) has an important impact on patient treatment and prognosis. We compared the diagnostic performance of high-sensitivity cardiac troponin T (hs-cTnT) and cardiac enriched microRNAs (miRNAs) in patients with MI. METHODS: Circulating concentrations of cardiac-enriched miR-208b and miR-499 were measured by quantitative PCR in a case-control study of 510 MI patients referred for primary mechanical reperfusion and 87 healthy controls. RESULTS: miRNA-208b and miR-499 were highly increased in MI patients (>10(5)-fold, P < 0.001) and nearly undetectable in healthy controls. Patients with ST-elevation MI (n= 397) had higher miRNA concentrations than patients with non-ST-elevation MI (n = 113) (P < 0.001). Both miRNAs correlated with peak concentrations of creatine kinase and cTnT (P < 10(-9)). miRNAs and hs-cTnT were already detectable in the plasma 1 h after onset of chest pain. In patients who presented <3 h after onset of pain, miR-499 was positive in 93% of patients and hs-cTnT in 88% of patients (P= 0.78). Overall, miR-499 and hs-cTnT provided comparable diagnostic value with areas under the ROC curves of 0.97. The reclassification index of miR-499 to a clinical model including several risk factors and hs-cTnT was not significant (P = 0.15). CONCLUSION: Circulating miRNAs are powerful markers of acute MI. Their usefulness in the establishment of a rapid and accurate diagnosis of acute MI remains to be determined in unselected populations of patients with acute chest pain.

Low levels of vascular endothelial growth factor B predict left ventricular remodeling after acute myocardial infarction.

BACKGROUND: Left ventricular (LV) remodeling is a prognostically important development after acute myocardial infarction (AMI). We recently reported that vascular endothelial growth factor B (VEGFB) may be a potential new biomarker of LV remodeling. This potential biomarker was evaluated in the present study. METHODS AND RESULTS: Patients with AMI (n = 290) and healthy volunteers (n = 42) were included. Plasma VEGFB levels were assessed before discharge. LV remodeling was determined by echocardiography at 6 months' follow-up. Levels of VEGFB were elevated in AMI patients compared with healthy volunteers (1.5-fold; P = .001). Mean plasma levels of VEGFB were 64% higher (P < .001) in patients in whom LV end-diastolic volume (EDV) decreased during follow-up (ΔEDV ≤ 0; n = 144; reverse remodeling) compared with patients in whom ΔEDV increased (ΔEDV > 0; n = 146; remodeling). Using logistic regression models, independent relationships were found between VEGFB (odds ratio [OR] 0.8, 95% confidence interval [CI] 0.7-0.9; P = .0007) and infarct territory (OR 1.7, 95% CI 1.1-2.8; P = .02). Patients with anterior MI and low levels of VEGFB had the highest risk of remodeling. VEFGB outperformed N-terminal pro-B-type natriuretic peptide to predict LV remodeling, and low levels of VEGFB (<100 pg/mL) provided a specificity of 90%. Adding VEGFB to a clinical model involving age, sex, smoking habit, and infarct territory resulted in a net reclassification index of 11.7%. CONCLUSIONS: Plasma levels of VEGFB increase after AMI and correlate with preservation of cardiac function. Low levels of VEGFB accurately predict LV remodeling. Therefore, circulating VEGFB may have clinical utility in the identification of patients at high risk of remodeling after AMI.

Regulation of N6-Methyladenosine after Myocardial Infarction.

Development of heart failure (HF) after myocardial infarction (MI) is responsible for premature death. Complex cellular and molecular mechanisms are involved in this process. A number of studies have linked the epitranscriptomic RNA modification N6-methyladenosine (m6A) with HF, but it remains unknown how m6A affects the risk of developing HF after MI. We addressed the regulation of m6A and its demethylase fat mass and obesity-associated (FTO) after MI and their association with HF. Using liquid chromatography coupled to mass spectrometry, we observed an increase of m6A content in the infarcted area of rat hearts subjected to coronary ligation and a decrease in blood. FTO expression measured by quantitative PCR was downregulated in the infarcted hearts. In whole blood samples collected at the time of reperfusion in MI patients, m6A content was lower in patients who developed HF as attested by a 4-month ejection fraction (EF) of ≤40% as compared to patients who did not develop HF (EF > 50%). M6A content was higher in females. These results show that m6A measured in blood is associated with HF development after MI and motivate further investigation of the potential role of m6A as a novel epitranscriptomics biomarker and therapeutic target of HF.

Association of miR-144 levels in the peripheral blood with COVID-19 severity and mortality.

Coronavirus disease-2019 (COVID-19) can be asymptomatic or lead to a wide symptom spectrum, including multi-organ damage and death. Here, we explored the potential of microRNAs in delineating patient condition and predicting clinical outcome. Plasma microRNA profiling of hospitalized COVID-19 patients showed that miR-144-3p was dynamically regulated in response to COVID-19. Thus, we further investigated the biomarker potential of miR-144-3p measured at admission in 179 COVID-19 patients and 29 healthy controls recruited in three centers. In hospitalized patients, circulating miR-144-3p levels discriminated between non-critical and critical illness (AUCmiR-144-3p = 0.71; p = 0.0006), acting also as mortality predictor (AUCmiR-144-3p = 0.67; p = 0.004). In non-hospitalized patients, plasma miR-144-3p levels discriminated mild from moderate disease (AUCmiR-144-3p = 0.67; p = 0.03). Uncontrolled release of pro-inflammatory cytokines can lead to clinical deterioration. Thus, we explored the added value of a miR-144/cytokine combined analysis in the assessment of hospitalized COVID-19 patients. A miR-144-3p/Epidermal Growth Factor (EGF) combined score discriminated between non-critical and critical hospitalized patients (AUCmiR-144-3p/EGF = 0.81; p < 0.0001); moreover, a miR-144-3p/Interleukin-10 (IL-10) score discriminated survivors from nonsurvivors (AUCmiR-144-3p/IL-10 = 0.83; p < 0.0001). In conclusion, circulating miR-144-3p, possibly in combination with IL-10 or EGF, emerges as a noninvasive tool for early risk-based stratification and mortality prediction in COVID-19.

Integrated protein network and microarray analysis to identify potential biomarkers after myocardial infarction.

A significant proportion of patients develop left ventricular (LV) dysfunction and heart failure (HF) after acute myocardial infarction (MI). Existing biomarkers of HF provide limited information after MI. To identify new prognostic biomarkers in MI patients, we designed an approach combining protein interaction networks and microarray analysis of blood cells. Blood samples for RNA and protein analysis were taken from 127 acute MI patients. Echocardiography was performed at one month. Assuming that angiogenesis is related to cardiac repair after MI, a protein-protein interaction network of angiogenesis was constructed and analyzed. Among the 556 proteins and 686 interactions of this network, a cluster of 53 proteins highly specialized in regulation of cell growth was identified. Of these 53 proteins, 38 were found differentially expressed by microarrays between low (< or = 40%) and high (>40%) LV ejection fraction (EF) patients (n = 32). Among these 38 genes, prediction analysis identified a set of three genes able to predict significant LV dysfunction (EF < or = 40%) with an area under the receiver operating characteristic curve (AUC) of 0.82. These three genes-vascular endothelial growth factor B, thrombospondin-1 and placental growth factor-had a stronger predictive value than brain natriuretic peptide and troponin T (AUC of 0.63). Independent validations on protein expression and quantitative PCR datasets confirmed the results. In conclusion, a new strategy is described that allows identifying new potential biomarkers. The three specific biomarkers described here remain to be validated in a larger patient population.

Adenosine up-regulates vascular endothelial growth factor in human macrophages.

It is known from animal models that the cardioprotective nucleoside adenosine stimulates angiogenesis mainly through up-regulation of vascular endothelial growth factor (VEGF). Since macrophages infiltrate the heart after infarction and because adenosine receptors behave differently across species, we evaluated the effect of adenosine on VEGF in human macrophages. Adenosine dose-dependently up-regulated VEGF expression and secretion by macrophages from healthy volunteers. VEGF production was also increased by blockade of extracellular adenosine uptake with dipyridamole. This effect was exacerbated by the toll-like receptor-4 ligands heparan sulfate, hyaluronic acid and lipopolysaccharide, and was associated with an increase of hypoxia inducible factor-1alpha expression, the main transcriptional inducer of VEGF in hypoxic conditions. The agonist of the adenosine A2A receptor CGS21680 reproduced the increase of VEGF and the antagonist SCH58261 blunted it. In conclusion, these results provide evidence that activation of adenosine A2A receptor stimulates VEGF production in human macrophages. This study suggests that adenosine is a unique pro-angiogenic molecule that may be used to stimulate cardiac repair.

Transcriptional networks characterize ventricular dysfunction after myocardial infarction: a proof-of-concept investigation.

There is currently no method powerful enough to identify patients at risk of developing ventricular dysfunction after myocardial infarction (MI). We aimed to identify major mechanisms related to ventricular dysfunction to predict outcome after MI. Based on the combination of domain knowledge, protein-protein interaction networks and gene expression data, a set of potential biomarkers of ventricular dysfunction after MI was identified. Here we propose a new strategy for the prediction of ventricular dysfunction after MI based on "network activity indices" (NAI), which encode gene network-based signatures and distinguishes between prognostic classes. These models outperformed prognostic models based on standard differential expression analysis. NAI-based models reported high classification accuracy, with a maximum area under the receiver operating characteristic curve (AUC) of 0.75. Furthermore, the classification capacity of these models was validated by performing evaluations on an independent patient cohort (maximum AUC=0.75). These results suggest that transcriptional network-based biosignatures can offer both powerful and biologically-meaningful prediction models of ventricular dysfunction after MI. This research reports a new integrative strategy for identifying transcriptional responses that characterize cardiac repair and for predicting clinical outcome after MI. It can be adapted to other clinical domains, such as those constrained by small molecular datasets and limited translational knowledge. Furthermore, it may reflect clinically-meaningful synergistic effects that cannot be identified by standard analyses.

Peripheral Blood RNA Levels of QSOX1 and PLBD1 Are New Independent Predictors of Left Ventricular Dysfunction After Acute Myocardial Infarction.

BACKGROUND: The identification of patients with acute myocardial infarction (MI) at risk of subsequent left ventricular (LV) dysfunction remains challenging, but it is important to optimize therapies. The aim of this study was to determine the unbiased RNA profile in peripheral blood of patients with acute MI and to identify and validate new prognostic markers of LV dysfunction. METHODS: We prospectively enrolled a discovery cohort with acute MI (n=143) and performed whole-blood RNA profiling at different time points. We then selected transcripts on admission that related to LV dysfunction at follow-up and validated them by quantitative polymerase chain reaction in the discovery cohort, in an external validation cohort (n=449), and in a representative porcine MI model with cardiac magnetic resonance-based measurements of infarct size and postmortem myocardial pathology (n=33). RESULTS: RNA profiling in the discovery cohort showed upregulation of genes involved in chemotaxis, IL (interleukin)-6, and NF-κB (nuclear factor-κB) signaling in the acute phase of MI. Expression levels of the majority of these transcripts paralleled the rise in cardiac troponin T and decayed at 30 days. RNA levels of QSOX1, PLBD1, and S100A8 on admission with MI correlated with LV dysfunction at follow-up. Using quantitative polymerase chain reaction, we confirmed that QSOX1 and PLBD1 predicted LV dysfunction (odds ratio, 2.6 [95% CI, 1.1-6.1] and 3.2 [95% CI, 1.4-7.4]), whereas S100A8 did not. In the external validation cohort, we confirmed QSOX1 and PLBD1 as new independent markers of LV dysfunction (odds ratio, 1.41 [95% CI, 1.06-1.88] and 1.43 [95% CI, 1.08-1.89]). QSOX1 had an incremental predictive value in a model consisting of clinical variables and cardiac biomarkers (including NT-proBNP [N-terminal pro-B-type natriuretic peptide]). In the porcine MI model, whole-blood levels of QSOX1 and PLBD1 related to neutrophil infiltration in the ischemic myocardium in an infarct size-independent manner. CONCLUSIONS: Peripheral blood QSOX1 and PLBD1 in acute MI are new independent markers of LV dysfunction post-MI.

Circulating levels of microRNA 423-5p are associated with 90 day mortality in cardiogenic shock.

AIMS: The role of microRNAs has not been studied in cardiogenic shock. We examined the potential role of miR-423-5p level to predict mortality and associations of miR-423-5p with prognostic markers in cardiogenic shock. METHODS AND RESULTS: We conducted a prospective multinational observational study enrolling consecutive cardiogenic shock patients. Blood samples were available for 179 patients at baseline to determine levels of miR-423-5p and other biomarkers. Patients were treated according to local practice. Main outcome was 90 day all-cause mortality. Median miR-423-5p level was significantly higher in 90 day non-survivors [median 0.008 arbitrary units (AU) (interquartile range 0.003-0.017) vs. 0.004 AU (0.002-0.009), P = 0.003]. miR-423-5p level above median was associated with higher lactate (median 3.7 vs. 2.4 mmol/L, P = 0.001) and alanine aminotransferase levels (median 68 vs. 35 IU/L, P < 0.001) as well as lower cardiac index (1.8 vs. 2.4, P = 0.04) and estimated glomerular filtration rate (56 vs. 70 mL/min/1.73 m2 , P = 0.002). In Cox regression analysis, miR-423-5p level above median was associated with 90 day all-cause mortality independently of established risk factors of cardiogenic shock [adjusted hazard ratio 1.9 (95% confidence interval 1.2-3.2), P = 0.01]. CONCLUSIONS: In cardiogenic shock patients, above median level of miR-423-5p at baseline is associated with markers of hypoperfusion and seems to independently predict 90 day all-cause mortality.

A 3-gene panel improves the prediction of left ventricular dysfunction after acute myocardial infarction.

BACKGROUND: Identification of patients at risk of poor outcome after acute myocardial infarction (MI) would allow tailoring healthcare to each individual. However, lack of prognostication tools renders this task challenging. Previous investigations suggested that blood transcriptome analysis may inform about prognosis after MI. We aim to independently confirm the value of gene expression profiles in the blood to predict left ventricular (LV) dysfunction after MI. METHODS AND RESULTS: Five genes (LMNB1, MMP9, TGFBR1, LTBP4 and TNXB) selected from previous studies were measured in peripheral blood samples obtained at reperfusion in 449 MI patients. 79 patients had LV dysfunction as attested by an ejection fraction (EF) ≤40% at 4-month follow-up and 370 patients had a preserved LV function (EF>40%). LMNB1, MMP9 and TGFBR1 were up-regulated in patients with LV dysfunction and LTBP4 was down-regulated, as compared with patients with preserved LV function. The 5 genes were significant univariate predictors of LV dysfunction. In multivariable analyses adjusted with traditional risk factors and corrected for model overfitting, a panel of 3 genes - TNXB, TGFBR1 and LTBP4 - improved the prediction of a clinical model (p=0.00008) and provided a net reclassification index of 0.45 [0.23-0.69], p=0.0002 and an integrated discrimination improvement of 0.05 [0.02-0.09], p=0.001. Bootstrap internal validation confirmed the incremental predictive value of the 3-gene panel. CONCLUSION: A 3-gene panel can aid to predict LV dysfunction after MI. Further independent validation is required before considering these findings for molecular diagnostic assay development.

The circular RNA MICRA for risk stratification after myocardial infarction.

BACKGROUND: A significant proportion of patients develop heart failure (HF) after acute myocardial infarction (MI). Predicting this development with novel biomarkers would allow tailoring healthcare to each individual. We recently identified a circular RNA called MICRA which was associated with HF development after MI. Here, we tested whether MICRA was able to risk stratify MI patients. METHODS: MICRA was assessed in whole blood samples collected at reperfusion in 472 patients with acute MI. Left ventricular ejection fraction (EF) was evaluated by echocardiography at 4 months. Multivariable analyses with ordinal regression were conducted to determine the ability of MICRA to classify patients into 3 EF groups: reduced EF (≤ 40%), mid-range EF (4149%) and preserved EF (≥ 50%). RESULTS: Eighty seven patients (18%) had a reduced EF, 106 (22%) had a mid-range EF and 279 (59%) had a preserved EF at 4 months. MICRA classified patients into EF groups with an adjusted odds ratio [95% confidence interval] of 0.78 [0.64-0.95]. MICRA improved the predictive value of a multivariable clinical model as attested by a decrease of the Akaike Information Criteria (p = 0.012). Bootstrap internal validation confirmed the incremental prognostic value of MICRA. CONCLUSION: We report that the circRNA MICRA improves risk classification after MI, supporting the added value of this novel biomarker in future prognostication strategies.

Incremental Value of Circulating MiR-122-5p to Predict Outcome after Out of Hospital Cardiac Arrest.

Rationale. The value of microRNAs (miRNAs) as biomarkers has been addressed in various clinical contexts. Initial studies suggested that miRNAs, such as the brain-enriched miR-124-3p, might improve outcome prediction after out-of-hospital cardiac arrest. The aim of this study is to determine the prognostic value of miR-122-5p in a large cohort of comatose survivors of out-of-hospital cardiac arrest. Methods. We analyzed 590 patients from the Targeted Temperature Management trial (TTM-trial). Circulating levels of miR-122-5p were measured in serum samples obtained 48 hours after return of spontaneous circulation. The primary end-point was poor neurological outcome at 6 months evaluated by the cerebral performance category score. The secondary end-point was survival at the end of the trial. Results. Forty-eight percent of patients had a poor neurological outcome at 6 months and 43% were dead at the end of the trial. Levels of miR-122-5p were lower in patients with poor neurological outcome compared to patients with good neurological outcome (p<0.001), independently of targeted temperature management regimen. Levels of miR-122-5p were significant univariate predictors of neurological outcome (odds ratios (OR), 95% confidence intervals (CI): 0.71 [0.57-0.88]). In multivariable analyses, miR-122-5p was an independent predictor of neurological outcome and improved the predictive value of a clinical model including miR-124-3p (integrated discrimination improvement of 0.03 [0.02-0.04]). In Cox proportional hazards models, miR-122-5p was a significant predictor of survival at the end of the trial. Conclusion. Circulating levels of miR-122-5p improve the prediction of outcome after out-of-hospital cardiac arrest.