Gene Expression Profiles of Peripheral Blood Mononuclear Cells Reveal Transcriptional Signatures as Novel Biomarkers for Cardiac Remodeling in Rats with Aldosteronism and Hypertensive Heart Disease

Identification of functional lncRNAs in atrial fibrillation based on RNA sequencing

BACKGROUND

Atrial fibrillation (AF) is one of the most common arrhythmia contributing to serious conditions such as stroke and heart failure. Recent studies demonstrated that long noncoding RNAs (lncRNAs) were related to cardiovascular disease. However, the molecular mechanisms of AF are not fully clear. This study intended to discover lncRNAs that are differentially expressed in AF compared with controls and evaluate the potential functions of these lncRNAs.

METHODS

Ninety-seven patients (49 patients with AF and 48 patients without AF) were included in this study. Among these patients, leucocyte suspensions of 3 AF patients and 3 controls were sent for RNA-seq analysis to select differentially expressed lncRNA and mRNA. Different lncRNA expressions were validated in another samples (46 AF patients and 45 controls). Gene ontology (GO) enrichment analysis was conducted to annotate the function of selected mRNAs. Alternative splicing (AS) analysis was performed and a lncRNA-mRNA network was also constructed. The receiver operating characteristics (ROC) curve was used to evaluate diagnostic values. Logistic regression analysis was utilized to assess the risk or protective factor of AF.

RESULTS

A total of 223 mRNAs and 105 lncRNAs were detected in AF patients compared with controls. Total 4 lncRNAs (LINC01781, AC009509.2, AL662844.3, AL662844.4) associated with AF were picked out for validation in another samples by quantitative real-time PCR (qRT-PCR), detecting that upregulated AC009509.2 and downregulated LINC01781 in AF patients. Multivariate logistic regression analysis illustrated that left atrial diameter (OR 1.201; 95% CI 1.093-1.320; P=0.000) and AC009509.2 (OR 1.732; 95% CI 1.092-2.747; P=0.020) were related to AF respectively. ROC curve showed that AC009509.2, LINC01781 and left atrial diameter (LAD) were predictors of AF. For LINC01781, the area under the curve (AUC) was 0.654 (95% CI 0.541-0.767, P=0.0113). For AC009509.2, the AUC was 0.710 (95% CI 0.599-0.822, P=0.0005). Bioinformatic methods (GO enrichment, AS analysis and lncRNA-mRNA network construction) were performed to reveal the role of lncRNAs.

CONCLUSIONS

This study discussed differentially expressed lncRNA and their potential interaction with mRNA in AF. LncRNA AC009509.2 could be a new potential biomarker for AF prediction.

Transcriptome-wide association study reveals novel susceptibility genes for coronary atherosclerosis

Background

Genetic risk factors substantially contributed to the development of coronary atherosclerosis. Genome-wide association study (GWAS) has identified many risk loci for coronary atherosclerosis, but the translation of these loci into therapeutic targets is limited for their location in non-coding regions. Here, we aimed to screen the potential coronary atherosclerosis pathogenic genes expressed though TWAS (transcriptome wide association study) and explore the underlying mechanism association.

Methods

Four TWAS approaches (PrediXcan, JTI, UTMOST, and FUSION) were used to screen genes associated with coronary atherosclerosis. Enrichment analysis of TWAS-identified genes was applied through the Metascape website. The summary-data-based Mendelian randomization (SMR) analysis was conducted to provide the evidence of causal relationship between the candidate genes and coronary atherosclerosis. At last, the cell type-specific expression of the intersection genes was examined by using human coronary artery single-cell RNA-seq, interrogating the immune microenvironment of human coronary atherosclerotic plaque at different stages of maturity.

Results

We identified 19 genes by at least three approaches and 1 gene (NBEAL1) by four approaches. Enrichment analysis enriching the genes identified at least by two TWAS approaches, suggesting that these genes were markedly enriched in asthma and leukocyte mediated immunity reaction. Further, the summary-data-based Mendelian randomization (SMR) analysis provided the evidence of causal relationship between NBEAL1 gene and coronary atherosclerosis, confirming the protecting effects of NBEAL1 gene and coronary atherosclerosis. At last, the single cell cluster analysis demonstrated that NBEAL1 gene has differential expressions in macrophages, plasma cells and endothelial cells.

Conclusion

Our study identified the novel genes associated with coronary atherosclerosis and suggested the potential biological function for these genes, providing insightful guidance for further biological investigation and therapeutic approaches development in atherosclerosis-related diseases.

Autophagy-mediated expression clusters are involved in immunity regulation of coronary artery disease

BACKGROUND

The association between autophagy and immunity, including infiltrating immunocytes, immune reaction gene-sets, and HLAs (human leukocyte antigen) gene, remains unclear. The present study aimed to provide a valid diagnostic tool for coronary artery disease (CAD), and explore the pathological mechanisms of CAD based on the association between autophagy and immunity.

METHODS

First, the overlap between differentially expressed genes (DEGs) and autophagy-related genes (ARGs) was identified. Subsequently, machine learning was conducted to screen risk genes closely related to CAD. Diverse autophagy phenotype-related clusters were identified using unsupervised clustering. The connections between different clusters and immune characteristics were evaluated as well.

RESULTS

The present study identified 27 differentially expressed autophagy-related genes (DEAGRs) in CAD samples compared with healthy conrtrols. A classifier constructing by 9 DEARGs was regarded as an effective diagnostic tool for CAD. Furthermore, three distinct autophagy phenotype - related clusters were identified, each cluster exhibited different immune characteristics. Finally, the gene ontology (GO) analysis of 901 autophagy phenotype-related genes showed that immune response, protein phosphorylation, and innate immune response were remarkable enrichment components.

CONCLUSIONS

This study identified an effective classifier constituted by 9-DEARGs that has good diagnostic performance for CAD, and revealed that autophagy and the immunity may be common critical factors in the occurrence and development of CAD.

The SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) in myalgic encephalomyelitis/chronic fatigue syndrome: A meta-analysis of public DNA methylation and gene expression data

People with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) often report a high frequency of viral infections and flu-like symptoms during their disease course. Given that this reporting agrees with different immunological abnormalities and altered gene expression profiles observed in the disease, we aimed at answering whether the expression of the human angiotensin-converting enzyme 2 (ACE2), the major cell entry receptor for SARS-CoV-2, is also altered in these patients. In particular, a low expression of ACE2 could be indicative of a high risk of developing COVID-19. We then performed a meta-analysis of public data on CpG DNA methylation and gene expression of this enzyme and its homologous ACE protein in peripheral blood mononuclear cells and related subsets. We found that patients with ME/CFS have decreased methylation levels of four CpG probes in the ACE locus (cg09920557, cg19802564, cg21094739, and cg10468385) and of another probe in the promoter region of the ACE2 gene (cg08559914). We also found a decreased expression of ACE2 but not of ACE in patients when compared to healthy controls. Accordingly, in newly collected data, there was evidence for a significant higher proportion of samples with an ACE2 expression below the limit of detection in patients than healthy controls. Altogether, patients with ME/CFS can be at a higher COVID-19 risk and, if so, they should be considered a priority group for vaccination by public health authorities. To further support this conclusion, similar research is recommended for other human cell entry receptors and cell types, namely, those cells targeted by the virus.

Unlocking the Value of White Blood Cells for Heart Failure Diagnosis

Cardiovascular disease (CVD) is the single greatest cause of mortality and morbidity worldwide. Inciting 85% of CVD fatalities is heart failure, often resulting in or from a myocardial infarction. Early detection along with pharmacological treatment and lifestyle adaptation can result in better prognosis. Biomarkers are molecular or physiological measures that indicate disease presence, status, and severity. However, not all forms of heart failure are created equal. Current mainstay biomarkers for heart failure, including NT-pro-BNP and ejection fraction, lack sensitivity for many patients. Circulating white blood cells and peripheral blood mononuclear cells (PBMCs) are emerging as surrogate biopsies, reflecting molecular changes in the heart. We discuss the advantages of PBMCs over other sources, as well as limitations and considerations. We urge medical center biobanks to collect, isolate and store circulating white blood cells as a rich source of biomarkers to catalyze the discovery of novel diagnostic tools for heart failure.

Transcriptomic Research in Heart Failure with Preserved Ejection Fraction: Current State and Future Perspectives

Heart failure with preserved ejection fraction (HFpEF) is increasing in incidence and has a higher prevalence compared with heart failure with reduced ejection fraction. So far, no effective treatment of HFpEF is available, due to its complex underlying pathophysiology and clinical heterogeneity. This article aims to provide an overview and a future perspective of transcriptomic biomarker research in HFpEF. Detailed characterisation of the HFpEF phenotype and its underlying molecular pathomechanisms may open new perspectives regarding early diagnosis, improved prognostication, new therapeutic targets and tailored therapies accounting for patient heterogeneity, which may improve quality of life. A combination of cross-sectional and longitudinal study designs with sufficiently large sample sizes are required to support this concept.

Association Between Inflammatory Markers and Myocardial Fibrosis

Inflammation promotes adverse ventricular remodeling. T1 mapping has been used to noninvasively assess interstitial myocardial fibrosis. We examined the association of baseline markers of systemic inflammation with interstitial myocardial fibrosis measured by extracellular volume fraction (ECV) and native T1 mapping at 10-year follow-up in the MESA (Multi-Ethnic Study of Atherosclerosis). Seven hundred seventy-two participants had complete baseline data and underwent cardiac magnetic resonance imaging. All analyses were stratified by sex. Multivariable linear regression models were constructed to assess the associations of baseline CRP (C-reactive protein), IL (interleukin)-6, and fibrinogen with native T1 time and ECV. Longer native T1 times and higher percentages of ECV represent increasing myocardial fibrosis. A 1-SD increment of log-transformed IL-6 levels was associated with 0.4% higher ECV in men (β=0.4; P=0.05). CRP and fibrinogen were not associated to ECV. A 1-SD increment in the log-transformed CRP levels was associated with 4.9 ms higher native T1 (β=4.9; P=0.03). In women, the inflammatory markers did not demonstrate association with native T1 nor ECV. Higher IL-6 and CRP levels are associated with increased interstitial myocardial fibrosis assessed by cardiac magnetic resonance in men. However, no inflammatory markers were associated to myocardial fibrosis in women.

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.

Gene scanning and heart attack risk

Coronary heart disease remains the leading cause of death in the Western World. The advent of microarray and next-generation sequencing technologies has generated multi-dimensional data sets, allowing for new pathophysiological insights into this complex disease. To date, genome-wide association studies (GWAS) have identified 152 associated loci and 320 candidate genes, contributing to the genetic risk of coronary artery disease (CAD) and acute myocardial infarction (AMI). The majority of single nucleotide polymorphisms (SNPs) mediate their risk by unknown mechanisms. A functional analysis based on Gene Ontology and KEGG pathways of candidate genes that are associated with CAD/AMI-SNPs showed the strongest evidence for genes regulating cholesterol metabolism. Additional clusters were significantly enriched for pathways, which play prominent roles during AMI and the development of atherosclerotic plaques in vascular tissue, including focal adhesion/extracellular matrix interaction, TGF-β signaling, apoptosis, regulation of vascular smooth muscle contraction, angiogenesis, calcium ion binding, and transcription factors. A systems genetics approach, which incorporates genetic risk with gene expression data, metabolomic data, and protein biochemistry into genome-wide network studies, holds promise to elucidate the complex interplay between genetic risk and environmental factors for coronary artery disease.

Expression Profiling of Circulating MicroRNAs in Canine Myxomatous Mitral Valve Disease

MicroRNAs (miRNAs) are small non-coding RNAs that have shown promise as noninvasive biomarkers in cardiac disease. This study was undertaken to investigate the miRNA expression profile in dogs with myxomatous mitral valve disease (MMVD). 277 miRNAs were quantified using RT-qPCR from six normal dogs (American College of Veterinary Internal Medicine Stage A), six dogs with MMVD mild to moderate cardiac enlargement (ACVIM Stage B1/B2) and six dogs with MMVD and congestive heart failure (ACVIM Stage C/D). Eleven miRNAs were differentially expressed (False Discovery Rate < 0.05). Dogs in Stage B1/B2 or C/D had four upregulated miRNAs, including three cfa-let-7/cfa-miR-98 family members, while seven others were downregulated, compared to Stage A. Expression of six of the 11 miRNAs also were significantly different between dogs in Stage C/D and those in Stage B1/B2. The expression changes were greater as disease severity increased. These miRNAs may be candidates for novel biomarkers and may provide insights into genetic regulatory pathways in canine MMVD.

Alterations in the expression of genes related to contractile function and hypertrophy of the left ventricle in chronically paced patients from the right ventricular apex

AIM

Long-term right ventricular apical (RVA) pacing may lead to left ventricular (LV) remodelling and heart failure. This study assessed changes in the expression of genes regulating LV contractile function and hypertrophy, after permanent RVA pacing and investigated whether such changes proceed or even predict LV remodelling.

METHODS AND RESULTS

We enrolled 52 consecutive patients (age 79.1 ± 7.7 years, 34 males) who underwent pacemaker implantation for bradycardic indications: Group A, 24 individuals with atrioventricular conduction disturbances and group B, 28 patients with sinus node disease. In group A, peripheral blood mRNA levels of gene sarcoplasmic reticulum calcium ATPase decreased at 3, 6, and 12 months' follow-up, while α-myosin heavy chain (MHC) decreased and β-MHC increased until 6 months follow-up. In this group, 25% of patients demonstrated significant LV remodelling. At 4 years, LV end-systolic diameter increased from 29.67 ± 3.39 mm at baseline to 35.38 ± 4.22 mm, LV end-diastolic diameter increased from 50 ± 4.95 to 56.71 ± 5.52 mm, and ejection fraction declined from 63.04 ± 10.22 to 52.83 ± 10.81%. Early alterations in gene expression were associated with a deterioration in LV function and geometry that became apparent months later. In group B, echocardiographic indexes and mRNA levels of the evaluated genes demonstrated no statistically significant changes.

CONCLUSIONS

Permanent RVA pacing in patients with preserved ejection fraction is associated with alterations in the expression of genes regulating LV contractile function and hypertrophy, measured in the peripheral blood. These alterations are traceable at an early stage, before echocardiographic changes are apparent and are associated with LV remodelling that becomes evident in the long term.

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.