Biomarkers identification for acute myocardial infarction detection via weighted gene co-expression network analysis

Expression characteristics of lipid metabolism-related genes and correlative immune infiltration landscape in acute myocardial infarction

Lipid metabolism is an important part of the heart's energy supply. The expression pattern and molecular mechanism of lipid metabolism-related genes (LMRGs) in acute myocardial infarction (AMI) are still unclear, and the link between lipid metabolism and immunity is far from being elucidated. In this study, 23 Common differentially expressed LMRGs were discovered in the AMI-related mRNA microarray datasets GSE61144 and GSE60993. These genes were mainly related to "leukotriene production involved in inflammatory response", "lipoxygenase pathway", "metabolic pathways", and "regulation of lipolysis in adipocytes" pathways. 12 LMRGs (ACSL1, ADCY4, ALOX5, ALOX5AP, CCL5, CEBPB, CEBPD, CREB5, GAB2, PISD, RARRES3, and ZNF467) were significantly differentially expressed in the validation dataset GSE62646 with their AUC > 0.7 except for ALOX5AP (AUC = 0.699). Immune infiltration analysis and Pearson correlation analysis explored the immune characteristics of AMI, as well as the relationship between these identified LMRGs and immune response. Lastly, the up-regulation of ACSL1, ALOX5AP, CEBPB, and GAB2 was confirmed in the mouse AMI model. Taken together, LMRGs ACSL1, ALOX5AP, CEBPB, and GAB2 are significantly upregulated in AMI patients' blood, peripheral blood of AMI mice, myocardial tissue of AMI mice, and therefore might be new potential biomarkers for AMI.

Effects of Subnormothermic Regulated Hepatic Reperfusion on Mitochondrial and Transcriptomic Profiles in a Porcine Model

OBJECTIVE

We sought to investigate the biological effects of pre-reperfusion treatments of the liver after warm and cold ischemic injuries in a porcine donation after circulatory death model.

SUMMARY OF BACKGROUND DATA

Donation after circulatory death represents a severe form of liver ischemia and reperfusion injury that has a profound impact on graft function after liver transplantation.

METHODS

Twenty donor pig livers underwent 60 minutes of in situ warm ischemia after circulatory arrest and 120 minutes of cold static preservation prior to simulated transplantation using an ex vivo perfusion machine. Four reperfusion treatments were compared: Control-Normothermic (N), Control- Subnormothermic (S), regulated hepatic reperfusion (RHR)-N, and RHR-S (n = 5 each). The biochemical, metabolic, and transcriptomic profiles, as well as mitochondrial function were analyzed.

RESULTS

Compared to the other groups, RHR-S treated group showed significantly lower post-reperfusion aspartate aminotransferase levels in the reperfusion effluent and histologic findings of hepatocyte viability and lesser degree of congestion and necrosis. RHR-S resulted in a significantly higher mitochondrial respiratory control index and calcium retention capacity. Transcriptomic profile analysis showed that treatment with RHR-S activated cell survival and viability, cellular homeostasis as well as other biological functions involved in tissue repair such as cytoskeleton or cytoplasm organization, cell migration, transcription, and microtubule dynamics. Furthermore, RHR-S inhibited organismal death, morbidity and mortality, necrosis, and apoptosis.

CONCLUSION

Subnormothermic RHR mitigates IRI and preserves hepatic mitochondrial function after warm and cold hepatic ischemia. This organ resuscitative therapy may also trigger the activation of protective genes against IRI. Sub- normothermic RHR has potential applicability to clinical liver transplantation.

Construction of the ceRNA network in the progression of acute myocardial infarction

Acute myocardial infarction (AMI) is a common disease that induced by sudden occlusion of a coronary artery and myocardial necrosis, which causes a great medical burden worldwide. Noncoding RNAs, such as circRNA, lncRNA and miRNA, play crucial roles in the progression of cardiovascular diseases. However, the circRNA-miRNA-mRNA network in the occurrence and development of AMI needs further investigation. In this study, we downloaded three AMI datasets, including circRNA (GSE160717), miRNA (GSE24591), and mRNA (GSE66360) from GEO database. The differentially expressed candidates, and GO and KEGG functions were analyzed by RStudio, and subsequently import to PPI and Cytoscape to obtain the hub genes. By using the starbase target prediction database, we further screen the ceRNA network of circRNA-miRNA-mRNA based on the selected differentially expressed candidates. We found 46 differential expressed mRNAs, 65 miRNAs, and five circRNAs. GO functions and KEGG enrichment of the 46 mRNAs focused on immune response and functions, involving IL-17 signaling pathway, Toll-like receptor signaling pathway, cytokine-cytokine receptor interaction, TNF signaling pathway, chemokine signaling pathway, and NF-kappaB signaling pathway, which may aggravate the pathologies of AMI. PPI and Cytoscape analysis showed 10 hub genes, including TLR2, IL1B, CCL4, CCL3, CCR5, TREM1, CXCL2, NLRP3, CSF3, and CCL20. By using starbase and circinteractome databases, ceRNA network construction showed that circRNA_023461 and circRNA_400027 regulate several miRNA-mRNA axes in AMI. In summary, this study uncovered the circRNA-miRNA-mRNA network based on three AMI datasets. The differentially expressed genes, including CCL20, CCL4, CSF3, and IL1B, focus on immune functions and pathways. Furthermore, circRNA_023461 and circRNA_400027 regulate several miRNA-mRNA axes, exerting important roles in AMI progression. Our founding provides new insights into AMI and improve the therapeutic strategies for AMI.

Identifying Genes Related to Acute Myocardial Infarction Based on Network Control Capability

Identifying genes significantly related to diseases is a focus in the study of disease mechanisms. In this paper, from the perspective of integrated analysis and dynamic control, a method for identifying genes significantly related to diseases based on logic networks constructed by the LAPP method, referred to as NCCM, is proposed and applied to the study of the mechanism of acute myocardial infarction (AMI). It is found that 82.35% of 17 differential control capability genes (DCCGs) identified by NCCM are significantly correlated with AMI/MI in the literature and DISEASES database. The enrichment analysis of DCCGs shows that AMI is closely related to the positive regulation of vascular-associated smooth muscle cell proliferation and regulation of cytokine production involved in the immune response, in which HBEGF, THBS1, NR4A3, NLRP3, EDN1, and MMP9 play a crucial role. In addition, although the expression levels of CNOT6L and ACYP1 are not significantly different between the control group and the AMI group, NCCM shows that they are significantly associated with AMI. Although this result still needs further verification, it shows that the method can not only identify genes with large differences in expression but also identify genes that are associated with diseases but with small changes in expression.

Potential therapeutic strategies for myocardial infarction: the role of Toll-like receptors

Myocardial infarction (MI) is a life-threatening condition among patients with cardiovascular diseases. MI increases the risk of stroke and heart failure and is a leading cause of morbidity and mortality worldwide. Several genetic and epigenetic factors contribute to the development of MI, suggesting that further understanding of the pathomechanism of MI might help in the early management and treatment of this disease. Toll-like receptors (TLRs) are well-known members of the pattern recognition receptor (PRR) family and contribute to both adaptive and innate immunity. Collectively, studies suggest that TLRs have a cardioprotective effect. However, prolonged TLR activation in the response to signals generated by damage-associated molecular patterns (DAMPs) results in the release of inflammatory cytokines and contributes to the development and exacerbation of myocardial inflammation, MI, ischemia-reperfusion injury, myocarditis, and heart failure. The objective of this review is to discuss and summarize the association of TLRs with MI, highlighting their therapeutic potential for the development of advanced TLR-targeted therapies for MI.

Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction

Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases worldwide. Advances in genomics have provided new ideas for the development of novel molecular biomarkers of potential clinical value for AMI.

Integrated Bioinformatics-Based Analysis of Hub Genes and the Mechanism of Immune Infiltration Associated With Acute Myocardial Infarction

Background

Acute myocardial infarction (AMI) is a fatal disease that causes high morbidity and mortality. It has been reported that AMI is associated with immune cell infiltration. Now, we aimed to identify the potential diagnostic biomarkers of AMI and uncover the immune cell infiltration profile of AMI.

Methods

From the Gene Expression Omnibus (GEO) data set, three data sets (GSE48060, GSE60993, and GSE66360) were downloaded. Differentially expressed genes (DEGs) from AMI and healthy control samples were screened. Furthermore, DEGs were performed via gene ontology (GO) functional and kyoto encyclopedia of genes and genome (KEGG) pathway analyses. The Gene set enrichment analysis (GSEA) was used to analyze GO terms and KEGG pathways. Utilizing the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) database, a protein–protein interaction (PPI) network was constructed, and the hub genes were identified. Then, the receiver operating characteristic (ROC) curves were constructed to analyze the diagnostic value of hub genes. And, the diagnostic value of hub genes was further validated in an independent data set GSE61144. Finally, CIBERSORT was used to represent the compositional patterns of the 22 types of immune cell fractions in AMI.

Results

A total of 71 DEGs were identified. These DEGs were mainly enriched in immune response and immune-related pathways. Toll-like receptor 2 (TLR2), interleukin-1B (IL1B), leukocyte immunoglobulin-like receptor subfamily B2 (LILRB2), Fc fragment of IgE receptor Ig (FCER1G), formyl peptide receptor 1 (FPR1), and matrix metalloproteinase 9 (MMP9) were identified as diagnostic markers with the value of p < 0.05. Also, the immune cell infiltration analysis indicated that TLR2, IL1B, LILRB2, FCER1G, FPR1, and MMP9 were correlated with neutrophils, monocytes, resting natural killer (NK) cells, gamma delta T cells, and CD4 memory resting T cells. The fractions of monocytes and neutrophils were significantly higher in AMI tissues than in control tissues.

Conclusion

TLR2, IL1B, LILRB2, FCER1G, FPR1, and MMP9 are involved in the process of AMI, which can be used as molecular biomarkers for the screening and diagnosis of AMI. In addition, the immune system plays a vital role in the occurrence and progression of AMI.

Screening for Regulatory Network of miRNA–Inflammation, Oxidative Stress and Prognosis-Related mRNA in Acute Myocardial Infarction: An in silico and Validation Study

Background

Acute myocardial infarction (AMI), which commonly leads to heart failure, is among the leading causes of mortality worldwide. The aim of this study was to find potential regulatory network for miRNA-inflammation, oxidative stress and prognosis-related mRNA to uncover molecular mechanisms of AMI.

Methods

The expression profiles of miRNA and mRNA in the blood samples from AMI patients were downloaded from the Gene Expression Omnibus (GEO) dataset for differential expression analysis. Weighted gene co-expression network analysis (WGCNA) was used to further identify important mRNAs. The negatively regulatory network construction of miRNA–inflammation, oxidative stress and prognosis-related mRNAs was performed, followed by protein–protein interaction (PPI) and functional analysis of mRNAs.

Results

A total of three pairs of negatively regulatory network of miRNA–inflammation and prognosis-related mRNAs (hsa-miR-636/hsa-miR-491-3p/hsa-miR-188-5p/hsa-miR-188-3p-AQP9, hsa-miR-518a-3p-C5AR1 and hsa-miR-509-3-5p/hsa-miR-127-5p-PLAUR), two pairs of negatively regulatory network of miRNA–oxidative stress and prognosis-related mRNAs (hsa-miR-604-TLR4 and hsa-miR-139-5p-CXCL1) and three pairs of negatively regulatory network of miRNA-inflammation, oxidative stress and prognosis-related mRNA (hsa-miR-634/hsa-miR-591-TLR2, hsa-miR-938-NFKBIA and hsa-miR-520h/hsa-miR-450b-3p-ADM) were identified. In the KEGG analysis, some signaling pathways were identified, such as complement and coagulation cascades, pathogenic Escherichia coli infection, chemokine signaling pathway and cytokine–cytokine receptor interaction and Toll-like receptor signaling pathway.

Conclusion

Identified negatively regulatory network of miRNA-inflammation/oxidative stress and prognosis-related mRNA may be involved in the process of AMI. Those inflammation/oxidative stress and prognosis-related mRNAs may be diagnostic and prognostic biomarkers for AMI.

Potential biomarkers of acute myocardial infarction based on co‑expression network analysis

Acute myocardial infarction (AMI) is a common cause of death in numerous countries. Understanding the molecular mechanisms of the disease and analyzing potential biomarkers of AMI is crucial. However, specific diagnostic biomarkers have thus far not been fully established and candidate regulatory targets for AMI remain to be determined. In the present study, the AMI gene chip dataset GSE48060 comprising blood samples from control subjects with normal cardiac function (n=21) and patients with AMI (n=26) was downloaded from Gene Expression Omnibus. The differentially expressed genes (DEGs) between the AMI and control groups were identified with the online tool GEO2R. The co-expression network of DEGs was analyzed by calculating the Pearson correlation coefficient of all gene pairs, mutual rank screening and cutoff threshold screening. Subsequently, the Gene Ontology (GO) database was used to analyze the genes' functions and pathway enrichment of genes in the most important modules was performed. Kyoto Encyclopedia of Genes and Genomes (KEGG) Disease and BioCyc were used to analyze the hub genes in the module to determine important sub-pathways. In addition, the expression of hub genes was confirmed by reverse transcription-quantitative PCR in AMI and control specimens. In the present study, 52 DEGs, including 26 upregulated and 26 downregulated genes, were identified. As key hub genes, three upregulated genes (AKR1C3, RPS24 and P2RY12) and three downregulated genes (ACSL1, B3GNT5 and MGAM) were identified from the co-expression network. Furthermore, GO enrichment analysis of all AMI co-expression network genes revealed functional enrichment mainly in ‘RAGE receptor binding’ and ‘negative regulation of T cell cytokine production’. In addition, KEGG Disease and BioCyc analysis indicated functional enrichment of the genes RPS24 and P2RY12 in ‘cardiovascular diseases’, of AKR1C3 in ‘cardenolide biosynthesis’, of MGAM in ‘glycogenolysis’, of B3GNT5 in ‘glycosphingolipid biosynthesis’ and of ACSL1 in ‘icosapentaenoate biosynthesis II’. In conclusion, the hub genes AKR1C3, RPS24, P2RY12, ACSL1, B3GNT5 and MGAM are potential markers of AMI, and have potential application value in the diagnosis of AMI.

Identification of key gene modules and pathways of human platelet transcriptome in acute myocardial infarction patients through co-expression network

Acute myocardial infarction (AMI) seriously threatens human life. In this study we aimed to systemically analyze the function of key gene modules in human platelets in AMI. We used weighted gene co-expression network analysis (WGCNA) to construct a co-expression module, and analyzed the relationship between potential modules and clinical characteristics based on platelet RNA-seq RPKM count reads of 16 ST-segment elevation myocardial infarction (STEMI) patients and 16 non-STEMI (NSTEMI) patients provided by the GEO database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed with the DAVID tool. Hub genes were calculated by the Cytohubba package. A total of 3653 genes was selected to construct the co-expression modules. A significant correlation between BMI and the module with color of sky-blue in STEMI. In NSTEMI, there was a significant correlation between the sky blue module and CAD, the Salmon module and HT, and the Cyan module and HT. In STEMI, the Hub genes were mainly enriched in functions related to cell membrane signal transduction including Aqp1, Armcx1, Gsta4, Hist3h2a and Il17re. In NSTEMI, the Hub genes are related mainly to energy metabolism in the sky-blue module including Olr1, Nap1l3, Gfer, Dohh, Crispld1 and Ccdc8b; they are mainly related to extracellular space and calcium binding in the Cyan module, including Clec12b, Chd4, Asgr1, Armcx4, Chid1 and Alkbh7. The hub genes in the Salmon module include Ell3, Aldh1b1, Cavin4, Cabp4, Eif1ay and Dus3l. Our results provide a framework for co-expression gene modules in STEMI and NSTEMI patients, and identify key targets as biomarkers for patients with different subtypes of AMI.

Regulation of Inflammation and Oxidative Stress by Formyl Peptide Receptors in Cardiovascular Disease Progression

G protein-coupled receptors (GPCRs) are the most important regulators of cardiac function and are commonly targeted for medical therapeutics. Formyl-Peptide Receptors (FPRs) are members of the GPCR superfamily and play an emerging role in cardiovascular pathologies. FPRs can modulate oxidative stress through nicotinamide adenine dinucleotide phosphate (NADPH) oxidase-dependent reactive oxygen species (ROS) production whose dysregulation has been observed in different cardiovascular diseases. Therefore, many studies are focused on identifying molecular mechanisms of the regulation of ROS production. FPR1, FPR2 and FPR3 belong to the FPRs family and their stimulation triggers phosphorylation of intracellular signaling molecules and nonsignaling proteins that are required for NADPH oxidase activation. Some FPR agonists trigger inflammatory processes, while other ligands activate proresolving or anti-inflammatory pathways, depending on the nature of the ligands. In general, bacterial and mitochondrial formylated peptides activate a proinflammatory cell response through FPR1, while Annexin A1 and Lipoxin A4 are anti-inflammatory FPR2 ligands. FPR2 can also trigger a proinflammatory pathway and the switch between FPR2-mediated pro- and anti-inflammatory cell responses depends on conformational changes of the receptor upon ligand binding. Here we describe the detrimental or beneficial effects of the main FPR agonists and their potential role as new therapeutic and diagnostic targets in the progression of cardiovascular diseases.

Dietary switch to Western diet induces hypothalamic adaptation associated with gut microbiota dysbiosis in rats

BACKGROUND

Early hyperphagia and hypothalamic inflammation encountered after Western diet (WD) are linked to rodent propensity to obesity. Inflammation in several brain structures has been associated with gut dysbiosis. Since gut microbiota is highly sensitive to dietary changes, we hypothesised that immediate gut microbiota adaptation to WD in rats is involved in inflammation-related hypothalamic modifications.

METHODS

We evaluated short-term impact of WD consumption (2 h, 1, 2 and 4 days) on hypothalamic metabolome and caecal microbiota composition and metabolome. Data integration analyses were performed to uncover potential relationships among these three datasets. Finally, changes in hypothalamic gene expression in absence of gut microbiota were evaluated in germ-free rats fed WD for 2 days.

RESULTS

WD quickly and profoundly affected the levels of several hypothalamic metabolites, especially oxidative stress markers. In parallel, WD consumption reduced caecal microbiota diversity, modified its composition towards pro-inflammatory profile and changed caecal metabolome. Data integration identified strong correlations between gut microbiota sub-networks, unidentified caecal metabolites and hypothalamic oxidative stress metabolites. Germ-free rats displayed reduced energy intake and no changes in redox homoeostasis machinery expression or pro-inflammatory cytokines after 2 days of WD, in contrast to conventional rats, which exhibited increased SOD2, GLRX and IL-6 mRNA levels.

CONCLUSION

A potentially pro-inflammatory gut microbiota and an early hypothalamic oxidative stress appear shortly after WD introduction. Tripartite data integration highlighted putative links between gut microbiota sub-networks and hypothalamic oxidative stress. Together with the absence of hypothalamic modifications in germ-free rats, this strongly suggests the involvement of the microbiota-hypothalamus axis in rat adaptation to WD introduction and in energy homoeostasis regulation.

Uncovering potential differentially expressed miRNAs and targeted mRNAs in myocardial infarction based on integrating analysis

Myocardial infarction (MI) is one of the leading causes of death globally. The aim of the present study was to find valuable microRNAs (miRNAs/miRs) and target mRNAs in order to contribute to our understanding of the pathology of MI. miRNA and mRNA data were downloaded for differential expression analysis. Then, a regulatory network between miRNAs and mRNAs was established, followed by function annotation of target mRNAs. Thirdly, prognosis and diagnostic analysis of differentially methylated target mRNAs were performed. Finally, an in vitro experiment was used to validate the expression of selected miRNAs and target mRNAs. A total of 19 differentially expressed miRNAs and 1,007 differentially expressed mRNAs were identified. Several regulatory interaction pairs between miRNA and mRNAs were identified, such as hsa-miR-142-2p-long-chain-fatty-acid-CoA ligase 1 (ACSL1), hsa-miR-15a-3p-nicotinamide phosphoribosyltransferase (NAMPT), hsa-miR-33b-5p-regulator of G-protein signaling 2 (RGS2), hsa-miR-17-3p-Jun dimerization protein 2 (JDP2), hsa-miR-24-1-5p-aquaporin-9 (AQP9) and hsa-miR-34a-5p-STAT1/AKT3. Of note, it was demonstrated that ACSL1, NAMPT, RGS2, JDP2, AQP9, STAT1 and AKT3 had diagnostic and prognostic values for patients with MI. In addition, STAT1 was involved in the ‘chemokine signaling pathway’ and ‘Jak-STAT signaling pathway’. AKT3 was involved in both the ‘MAPK signaling pathway’ and ‘T cell receptor signaling pathway’. Reverse transcription-quantitative PCR validation of hsa-miR-142-3p, hsa-miR-15a-3p, hsa-miR-33b-5p, ACSL1, NAMPT, RGS2 and JDP2 expression was consistent with the bioinformatics analysis. In conclusion, the identified miRNAs and mRNAs may be involved in the pathology of MI.

Extracellular granzyme A in amniotic fluid is elevated in the presence of sterile intra-amniotic inflammation in preterm prelabor rupture of membranes

INTRODUCTION

To determine the levels of granzyme A in amniotic fluid in pregnancies complicated by preterm prelabor rupture of membranes (PPROM), based on the presence of microbial invasion of the amniotic cavity (MIAC) and/or intra-amniotic inflammation (IAI).

METHODS OF STUDY

A total of 166 women with singleton pregnancies complicated by PPROM were included. Amniocentesis was performed at the time of admission and assessments of MIAC (using both cultivation and non-cultivation techniques) and IAI (interleukin-6 in amniotic fluid) were performed on all subjects. Based on the presence/absence of MIAC and IAI, the women were further divided into the following subgroups: intra-amniotic infection, sterile IAI, colonization, and absence of both MIAC and IAI. Amniotic fluid granzyme A levels were assessed using ELISA.

RESULTS

Women with MIAC had lower levels of granzyme A in the amniotic fluid than women without this condition (with MIAC: median 15.9 pg/mL vs. without MIAC: median 19.9 pg/mL, p = .03). Women with sterile IAI had higher amniotic fluid granzyme A levels than women with intra-amniotic infection, colonization and women with the absence of either MIAC or IAI (intra-amniotic infection: median 15.6 pg/mL; sterile IAI: median 31.8 pg/mL; colonization: median 16.9 pg/mL; absence of both MIAC and IAI: median 18.8 pg/mL; p = .02).

CONCLUSIONS

The presence of sterile IAI was associated with elevated levels of granzyme A in amniotic fluid.

Identification of Post-myocardial Infarction Blood Expression Signatures Using Multiple Feature Selection Strategies

Myocardial infarction (MI) is a type of serious heart attack in which the blood flow to the heart is suddenly interrupted, resulting in injury to the heart muscles due to a lack of oxygen supply. Although clinical diagnosis methods can be used to identify the occurrence of MI, using the changes of molecular markers or characteristic molecules in blood to characterize the early phase and later trend of MI will help us choose a more reasonable treatment plan. Previously, comparative transcriptome studies focused on finding differentially expressed genes between MI patients and healthy people. However, signature molecules altered in different phases of MI have not been well excavated. We developed a set of computational approaches integrating multiple machine learning algorithms, including Monte Carlo feature selection (MCFS), incremental feature selection (IFS), and support vector machine (SVM), to identify gene expression characteristics on different phases of MI. 134 genes were determined to serve as features for building optimal SVM classifiers to distinguish acute MI and post-MI. Subsequently, functional enrichment analyses followed by protein-protein interaction analysis on 134 genes identified several hub genes (IL1R1, TLR2, and TLR4) associated with progression of MI, which can be used as new diagnostic molecules for MI.

Key miRNAs associated with memory and learning disorder upon exposure to sevoflurane determined by RNA sequencing

The study aimed to identify differentially expressed microRNAs (miRNAs/miRs) and explore the mechanisms governing impaired memory and learning ability in developing brains exposed to sevoflurane. A total of six 7‑day‑old male ICR mice were randomly assigned into the sevoflurane anesthesia group (treated with 2.4% sevoflurane) or control group (treated with normal saline solution at the same dose). After 14 days, the mice were subjected to a Morris water maze experiment. Then, the animals were sacrificed and hippocampus tissues were isolated. RNAs in hippocampus tissues were sequenced and the differential miRNA expression profiles were identified by a bioinformatics approach. The learning and memory function of mice were significantly affected by sevoflurane exposure. A total of 18 miRNAs were found to be significantly affected by sevoflurane administration. Their target genes clustered into different functional groups, such as 'dephosphorylation', 'vesicle localization' and the 'Wnt signaling pathway'. miR‑101b‑3p was closely related with 'chromatin binding' and 'protein serine/threonine kinase activity'. The most represented pathways for miRNAs included 'neuroactive ligand‑receptor interaction' (miR‑1187), 'long‑term depression' (miR‑425‑5p), 'FoxO signaling pathway' (miR‑425‑5p) and the 'neurotrophin signaling pathway' (miR‑467a‑3p). miR‑467a‑3p (degree=89), miR‑101b‑3p (degree=59), and miR‑1187 (degree=51) were the hub nodes in the miRNA regulatory network. The Wnt signaling pathway, miR‑467a‑3p, miR‑1187 and miR‑101b‑3p may be therapeutic targets for preventing cognitive impairments induced by sevoflurane.

Weighted Gene Co-Expression Network Analysis Identifies Critical Genes in the Development of Heart Failure After Acute Myocardial Infarction

Background: The development of heart failure (HF) remains a common complication following an acute myocardial infarction (AMI), and is associated with substantial adverse outcomes. However, the specific predictive biomarkers and candidate therapeutic targets for post-infarction HF have not been fully established. We sought to perform a weighted gene co-expression network analysis (WGCNA) to identify key modules, hub genes, and possible regulatory targets involved in the development of HF following AMI.

Methods: Genes exhibiting the most (top 50%) variation in expression levels across samples in a GSE59867 dataset were imported to the WGCNA. Gene Ontology and pathway enrichment analyses were performed on genes identified in the key module by Metascape. Gene regulatory networks were constructed using the microarray probe reannotation and bioinformatics database. Hub genes were screened out from the key module and validated using other datasets.

Results: A total of 10,265 most varied genes and six modules were identified between AMI patients who developed HF within 6 months of follow-up and those who did not. Specifically, the blue module was found to be the most significantly related to the development of post-infarction HF. Functional enrichment analysis revealed that the blue module was primarily associated with the inflammatory response, immune system, and apoptosis. Seven transcriptional factors, including SPI1, ZBTB7A, IRF8, PPARG, P65, KLF4, and Fos, were identified as potential regulators of the expression of genes identified in the blue module. Further, non-coding RNAs, including miR-142-3p and LINC00537, were identified as having close interactions with genes from the blue module. A total of six hub genes (BCL3, HCK, PPIF, S100A9, SERPINA1, and TBC1D9B) were identified and validated for their predictive value in identifying future HFs.

Conclusions: By using the WGCNA, we provide new insights into the underlying molecular mechanism and molecular markers correlated with HF development following an AMI, which may serve to improve risk stratification, therapeutic decisions, and prognosis prediction in AMI patients.

Dysregulated expression of STAT1, miR-150, and miR-223 in peripheral blood mononuclear cells of coronary artery disease patients with significant or insignificant stenosis

Coronary artery disease (CAD) is a multicellular disease characterized by chronic inflammation. Peripheral blood-mononuclear cells (PBMCs), as a critical component of immune system, actively cross-talk with pathophysiological conditions induced by endothelial cell injury, reflecting in perturbed PBMC expression. STAT1 is believed to be relevant to CAD pathogenesis through regulating key inflammatory processes and modulating STAT1 expression play key roles in fine-tuning CAD-related inflammatory processes. This study evaluated PBMC expressions of STAT1, and its regulators (miR-150 and miR-223) in a cohort including 72 patients with CAD with significant ( ≥ 50%) stenosis, 30 patients with insignificant ( < 50%) coronary stenosis (ICAD), and 74 healthy controls, and assessed potential of PBMC expressions to discriminate between patients and controls. We designed quantitative real-time polymerase chain reaction (RT-qPCR) assays and identified stable reference genes for normalizing PBMC quantities of miR-150, miR-223, and STAT1 applying geNorm algorithm to six small RNAs and five mRNAs. There was no significant difference between CAD and ICAD patients regarding STAT1 expression. However, both groups of patients had higher levels of STAT1 than healthy controls. miR-150 and miR-223 were differently expressed across three groups of subjects and were downregulated in patients compared with healthy controls, with the lowest expression levels being observed in patients with ICAD. ROC curves suggested that PBMC expressions may separate between different groups of study subjects. PBMC expressions also discriminated different clinical manifestations of CAD from ICADs or healthy controls. In conclusion, the present study reported PBMC dysregulations of STAT1, miR-150, and miR-223, in patients with significant or insignificant coronary stenosis and suggested that these changes may have diagnostic implications.

Identification of key genes involved in myocardial infarction

Background

This study focuses on the identification of conserved genes involved in myocardial infarction (MI), and then analyzed the differentially expressed genes (DEGs) between the incident and recurrent events to identify MI-recurrent biomarkers.

Methods

Gene expression data of MI peripheral blood were downloaded from GSE97320 and GSE66360 datasets. We identified the common DEGs in these two datasets by functional enrichment analysis and protein–protein interaction (PPI) network analysis. GSE48060 was further analyzed to validate the conserved genes in MI and to compare the DEGs between the incident and recurrent MI.

Results

A total of 477 conserved genes were identified in the comparison between MI and control. Protein–protein interaction (PPI) network showed hub genes, such as MAPK14, STAT3, and MAPKAPK2. Part of those conserved genes was validated in the analysis of GSE48060. The DEGs in the incident and recurrent MI showed significant differences, including RNASE2 and A2M-AS1 as the potential biomarkers of MI recurrence.

Conclusions

The conserved genes in the pathogenesis of MI were identified, benefit for target therapy. Meanwhile, some specific genes may be used as markers for the prediction of recurrent MI.

Electronic supplementary material

The online version of this article (10.1186/s40001-019-0381-x) contains supplementary material, which is available to authorized users.