Coronary Heart Disease Biomarkers Research Articles

Unraveling the intricate physiological processes dysregulated in CHD-affected and Dan-Lou tablet-treated individuals

Coronary heart disease (CHD), a multifactorial cardiovascular condition, arises from the accumulation of atherosclerotic plaque in the coronary arteries, resulting in compromised blood flow to the heart and complications such as angina, myocardial infarction, or heart failure. Addressing global prevalence, risk factors, and genetics is crucial for effective management. The current study aims to identify molecular biomarkers for CHD by scrutinizing the expression patterns of differentially expressed genes (DEGs), utilizing various bioinformatic tools. In this investigation, a total of 24 samples underwent examination using the GEO2R tool. These included eight samples from individuals before treatment (GSM5434123-30), eight samples from patients after Dan-Lou tablet treatment (GSM5434131-38), and eight samples from healthy control subjects (GSM5434139-46). A suite of bioinformatics tools was used to detect enriched genes within the network, namely, Cytoscape (v3.10.1) and Molecular Complex Detection (MCODE). Functional analysis of the DEGs was conducted via clusterProfiler, a R-based package, and ClueGO. 182 and 174 DEGs corresponding to untreated and treated patient sample groups were functionally annotated for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. ARF6 gene dysregulation was implicated in the myeloid cell apoptotic process (GO:0033028), regulation of actin cytoskeleton (hsa:04810), and other vital cellular functions. The myeloid cell apoptotic process (GO:0033028) was also observed to be regulated by the differential expression of the STAT5B gene. Additionally, STAT5B was found to be associated with the regulation of erythrocyte differentiation (GO:0045646). Providing targeted therapy based on the patient's idiosyncratic gene expression profiles could lead to the curing of various disorders in the near future.

Combinatory data-independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities.

Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra-performance liquid chromatography-high-resolution mass spectrometry in data-independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high-throughput characterization of plasma lipids. The results also improved our understanding of metabolic disorders of CHD and its comorbidities, which can provide valuable suggestions for medical intervention.

Identification of Plasma Exosomes hsa_circ_0001360 and hsa_circ_0000038 as Key Biomarkers of Coronary Heart Disease.

Coronary heart disease (CHD) is the leading cause of death and disability worldwide. Accumulating evidence reveals that atherosclerosis (AS), characterized by systemic, chronic, and multifocal disease, and is the primary pathological basis of cardiovascular diseases, including CHD. However, the molecular underpinnings of CHD are still far from well understood. Our study attempted to identify aberrant plasma exosome-derived circRNAs and key exosomal circRNA biomarkers for CHD. The expression profiles of mRNAs, circRNAs, and lncRNAs in the blood exosomes of CHD patients and healthy controls were obtained from the exoRBase database. The corresponding miRNAs of the differentially expressed mRNAs, circRNAs, and lncRNAs were predicted via ENCORI and the miRcode database. LncRNAs/circRNAs and mRNAs with the cotargeted miRNAs were selected to construct an interaction network. Multiple machine learning algorithms have been used to explore potential biomarkers, followed by verification in patients with CHD using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). Based on the cutoff criterion of P < 0.05, we identified 85 differentially expressed circRNAs (4 upregulated and 81 downregulated), 43 differentially expressed lncRNAs (24 upregulated and 19 downregulated), and 312 differentially expressed mRNAs (55 upregulated and 257 downregulated). Functional enrichment analysis revealed that the differentially expressed mRNAs were involved mainly in neutrophil extracellular trap (NET) formation and the nucleotide-binding oligomerization domain- (NOD-) like receptor signaling pathway. Further analysis revealed that the DEGs in the circRNA/lncRNA-miRNA-mRNA interaction network were closely related to lipid and atherosclerotic signaling pathways. Hsa_circ_0001360 and hsa_circ_0000038 were identified as potential biomarkers for CHD based on three machine learning algorithms. The relative expression levels of hsa_circ_0001360 and hsa_circ_0000038 were significantly altered in plasma exosomes from patients with CHD. ROC curve analysis revealed that the areas under the curve (AUCs) were 0.860, 0.870, and 0.940 for hsa_circ_0001360, hsa_circ_0000038, and the two-gene combination, respectively. The circRNA/lncRNA-miRNA-mRNA interaction network might help to elucidate the pathogenesis of CHD. Hsa_circ_0001360 combined with hsa_circ_0000038 might be an important diagnostic biomarker.

Characterization of lncRNA-associated ceRNA network to uncover novel potential biomarkers in coronary artery disease.

The purpose of this study was to construct a competitive endogenous RNA (ceRNA) network related to long non-coding RNA (lncRNAs) via the bioinformatics analysis, reveal the pathogenesis of coronary heart disease (CAD) and develop new biomarkers for CAD. The gene expression datasets of peripheral blood of CAD were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed mRNAs, miRNAs and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) were identified. Subsequently, a ceRNA network involving lncRNAs, miRNAs, and mRNAs was built. Moreover, DElncRNAs in the cytoplasm were screened and a DElncRNA-associated ceRNA network was established. In total, 1860 DEmRNAs, 393 DElncRNAs and 20 DEmiRNAs were filtrated in patients with CAD compared with normal controls. Functional analysis suggested that DEmRNAs significantly enriched in CAD-related pathways, such as PI3K-Akt signaling pathways and MAPK signaling pathway. The ceRNA network contained 12 DEmiRNAs, 30 DElncRNAs and 537 DEmRNAs. Afterwards, the cytoplasm ceRNA network was consisted of 537 DEmRNAs, 12 DEmiRNAs and 12 DElncRNAs. Such as, up-regulated LncRNA-HOX transcript antisense RNA (HOTAIR) was interacted with down-regulated has-miR-326 and has-miR-1. The successful construction of lncRNA-associated ceRNA network is helpful to better clarify the pathogenesis of CAD and provide potential peripheral blood biomarkers for CAD.

Identification of an association between coronary heart disease and ITGB2 methylation in peripheral blood by a case-control study

BackgroundBlood DNA methylation was associated with coronary heart disease (CHD) risk in Caucasians. We investigated the association between DNA methylation in peripheral blood at the reported loci and CHD in the Chinese population. MethodsThe integrin subunit beta 2 (ITGB2) gene was identified in 196 CHD cases and 184 controls, and its methylation level was determined by mass spectrometry. Logistic regression was used to assess the association. ResultsHypomethylation of ITGB2 was significantly associated with heart failure CHD and NYHA Ⅰ&Ⅱ CHD patients with minor to medium cardiac function impairment (ITGB2_CpG_11/cg08422803, OR per −10 % methylation = 1.15 and 1.16; p = 0.012 and 0.018 by Bonferroni correction, respectively). Hypomethylation of ITGB2_CpG_11/cg08422803 was a risk factor for CHD in people < 65 years and males (p < 0.05 after Bonferroni correction). The combination of ITGB2 methylation and conventional CHD risk factors could efficiently discriminate CHD, heart failure CHD, NYHA I&II CHD, and myocardial infarction CHD patients from controls (AUC = 0.78, 0.81, 0.80, and 0.81, respectively). ConclusionBlood-based ITGB2 methylation has the potential as a biomarker for CHD. The combination of ITGB2 methylation and conventional CHD risk factors may improve the risk assessment and detection of CHD.

Integration of Biomarker Polygenic Risk Score Improves Prediction of Coronary Heart Disease

There are several established biomarkers for coronary heart disease (CHD), including blood pressure, cholesterol, and lipoproteins. It is of high interest to determine how a combined polygenic risk score (PRS) of CHD-associated biomarkers (BioPRS) can further improve genetic prediction of CHD. We developed CHDBioPRS, combining BioPRS with PRS of CHD in the UK Biobank and tested it on FinnGen. We found that BioPRS was clearly predictive of CHD and that CHDBioPRS improved the standard CHD PRS. The largest effect was observed with early onset cases in FinnGen, with HRs above 2 per standard deviation of CHDBioPRS.

Improving the Data Quality of Untargeted Metabolomics through a Targeted Data-Dependent Acquisition Based on an Inclusion List of Differential and Preidentified Ions.

Metabolomics based on high-resolution mass spectrometry has become a powerful technique in biomedical research. The development of various analytical tools and online libraries has promoted the identification of biomarkers. However, how to make mass spectrometry collect more data information is an important but underestimated research topic. Herein, we combined full-scan and data-dependent acquisition (DDA) modes to develop a new targeted DDA based on the inclusion list of differential and preidentified ions (dpDDA). In this workflow, the MS1 datasets for statistical analysis and metabolite preidentification were first obtained using full-scan, and then, the MS/MS datasets for metabolite identification were obtained using targeted DDA of quality control samples based on the inclusion list. Compared with the current methods (DDA, data-independent acquisition, targeted DDA with time-staggered precursor ion list, and iterative exclusion DDA), dpDDA showed better stability, higher characteristic ion coverage, higher differential metabolites' MS/MS coverage, and higher quality MS/MS spectra. Moreover, the same trend was verified in the analysis of large-scale clinical samples. More surprisingly, dpDDA can distinguish patients with different severities of coronary heart disease (CHD) based on the Canadian Cardiovascular Society angina classification, which we cannot distinguish through conventional metabolomics data collection. Finally, dpDDA was employed to differentiate CHD from healthy control, and targeted metabolomics confirmed that dpDDA could identify a more complete metabolic pathway network. At the same time, four unreported potential CHD biomarkers were identified, and the area under the receiver operating characteristic curve was greater than 0.85. These results showed that dpDDA would expand the discovery of biomarkers based on metabolomics, more comprehensively explore the key metabolites and their association with diseases, and promote the development of precision medicine.

Serum soluble TREM2 is an independent biomarker associated with coronary heart disease

BackgroundTriggering receptor expressed on myeloid cells 2 (TREM2) is a unique receptor expressed by macrophages in atherosclerotic plaque and is involved in the progression of atherosclerosis. Whether serum soluble TREM2 (sTREM2) levels has a relationship with coronary heart disease (CHD) remains unclear. MethodsThe cross-sectional study included 86 patients with CHD and 86 controls matched with age and sex. Demographic information, medication history, and laboratory data were collected. sTREM2 concentrations were detected by enzyme-linked immunosorbent assay. We compared the sTREM2 levels in two groups and constructed stepwise linear regression analysis for factors related to the sTREM2 level in patients with CHD; we further used the logistic regression model to evaluate the relationship between sTREM2 and CHD. The diagnostic value of sTREM2 and other biomarkers in CHD was evaluated by the receiver operating characteristic curve (ROC). ResultsThe serum level of sTREM2 in CHD patients is higher than that in controls. In CHD patients, the stepwise linear regression analysis found that sTREM2 levels were correlated with triglyceride (TG), high-density lipoprotein cholesterols (HDL-C), apolipoprotein B (ApoB) and smoking status. Logistic regression models showed that sTREM2 was associated independently with CHD after adjusted confounders. The ROC curve showed a sensitivity of 59.3% and specificity of 81.4% with an area under the curve of 0.781 (95% CI: 0.711–0.852) for the diagnosis of CHD with serum sTREM2 at a cut-off value of > 1104.894 pg/ml, indicating a higher diagnostic value than high sensitivity C reaction protein (hs-CRP) and apolipoprotein B (ApoB). ConclusionIn this study, we provide evidence that sTREM2 levels are elevated in CHD patients and are associated with various cardiovascular risk factors. Additionally, sTREM2 demonstrates better diagnostic performance compared to traditional indicators in identifying CHD. These findings suggest that sTREM2 may serve as a potential biomarker for coronary heart disease.

Ectodomain Shedding by ADAM17 Increases the Release of Soluble CD40 from Human Endothelial Cells under Pro-Inflammatory Conditions.

Homozygosity for the C allele of the -1T>C single nucleotide polymorphism (SNP) of the CD40 gene (rs1883832) is associated with susceptibility to coronary heart disease (CHD), enhanced CD40 expression, and shedding. The disintegrin metalloprotease ADAM17 can cleave various cell surface proteins. This study investigates an association between ADAM17-mediated CD40 shedding and inflammation in CC genotype human endothelial cells. Human umbilical vein endothelial cells (HUVEC) carrying the CC genotype were stimulated with soluble CD40 ligand (sCD40L) or tumor necrosis factor-α (TNFα). Messenger RNA and protein expression were determined with standard methods. Levels of high sensitive c-reactive protein (hs-CRP), interleukin-6 (IL-6), and sCD40 in plasma samples from patients with CHD were assessed using ELISA. ADAM17 surface abundance was elevated following stimulation with CD40L and TNFα just as its regulator iRhom2. Inhibition of ADAM17 prevented TNFα-induced sCD40 and soluble vascular cell adhesion molecule-1 release into the conditioned medium and reinforced CD40 surface abundance. Secondary to inhibition of ADAM17, stimulation with CD40L or TNFα upregulated monocyte chemoattractant protein-1 mRNA and protein. Levels of sCD40 and the inflammatory biomarkers hs-CRP and IL-6 were positively correlated in the plasma of patients with CHD. We provide a mechanism by which membrane-bound CD40 is shed from the endothelial cell surface by ADAM17, boosting sCD40 formation and limiting downstream CD40 signaling. Soluble CD40 may represent a robust biomarker for CHD, especially in conjunction with homozygosity for the C allele of the -1T>C SNP of the CD40 gene.

Identification of circulating T-cell immunoglobulin and mucin domain 4 as a potential biomarker for coronary heart disease.

Efferocytosis, the process of engulfing and removing apoptotic cells, is attenuated in vulnerable plaques of advanced atherosclerosis. T-cell immunoglobulin and mucin domain 4 (TIMD4) is a recognition receptor protein for efferocytosis that has been implicated in atherosclerosis mouse models. However, the role of serum-soluble TIMD4 (sTIMD4) in coronary heart disease (CHD) remains unknown. In this study, we analyzed serum samples collected from two groups: Group 1 (36 healthy controls and 70 CHD patients) and Group 2 (44 chronic coronary syndrome [CCS]) and 81 acute coronary syndrome [ACS] patients). We found that sTIMD4 levels in patients with CHD were significantly higher than those in healthy controls and were also higher in ACS than in CCS patients. The area under the receiver operating characteristic curve was 0.787. Furthermore, our in vitro results showed that low-density lipoprotein/lipopolysaccharide activated p38 mitogen-activated protein kinase, which in turn enhanced a disintegrin and metalloproteinase 17, resulting in increased secretion of sTIMD4. This impairment of macrophage efferocytosis promoted inflammation. Thus, this study is not only the first identification of a potential novel biomarker of CHD, sTIMD4, but also demonstrated its pathogenesis mechanism, providing a new direction for the diagnosis and treatment of CHD.

Effect of cognitive processing therapy on markers of cardiovascular risk in posttraumatic stress disorder patients: A randomized clinical trial

ObjectivePosttraumatic stress disorder (PTSD) is associated with elevated risk of coronary heart disease (CHD); however, the effects of PTSD treatment on CHD biomarkers is unknown. This study examined whether cognitive processing therapy (CPT) improves 24-hourheart rate variability (HRV), a predictor of CHD mortality. MethodsIndividuals between the ages of 40 and 65 years with PTSD (n = 112) were randomized to receive 12 sessions of CPT or a Waiting List (WL) intervention comprised of 6 weekly telephone checks of emotional status. The primary outcome variable was 24-hour HRV estimated from the standard deviation of all normal R-R intervals (SDNN); secondary outcomes were the root mean square of successive differences between heart beats (RMSSD), low-frequency HRV (LF-HRV) and high-frequency HRV (HF-HRV). Secondary outcomes also included 24-hour urinary catecholamine excretion, plasma C-reactive protein (CRP), and flow-mediated dilation (FMD) of the brachial artery. For outcomes, linear mixed longitudinal models were used to estimate mean differences (Mdiff). ResultsParticipants randomized to the CPT group did not show improved SDNN (Mdiff = 9.8; 95%CI, −2.7 to 22.3; p = 0.12), the primary outcome variable, but showed improved RMSSD (Mdiff = 3.8; 95% CI, 0.5 to 7.1; p = 0.02), LF- HRV (Mdiff =0.3; 95% CI, 0.1 to 0.5; p = 0.01), and HF-HRV (Mdiff = 0.3; 95% CI, 0.0 to 0.6; p = 0.03) compared to WL. There were no differences between groups in catecholamine excretion, FMD, or inflammatory markers. ConclusionTreating PTSD may not only improve quality of life but may also help ameliorate heightened CHD risk characteristics of PTSD.

Integrated strategy for biomarkers of stable coronary heart disease with phlegm and blood stasis syndrome based on RNA-seq and network pharmacology

This study aimed to analyze the biological foundation and biomarkers of stable coronary heart disease(CHD) with phlegm and blood stasis(PBS) syndrome based on RNA-seq and network pharmacology. Peripheral blood nucleated cells from five CHD patients with PBS syndrome, five CHD patients with non-PBS syndrome, and five healthy adults were collected for RNA-seq. The specific targets of CHD with PBS syndrome were determined by differential gene expression analysis and Venn diagram analysis. The active ingredients of Danlou Tablets were screened out from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, and the &quot;component-target&quot; prediction was completed through PubChem and SwissTargetPrediction. The &quot;drug-ingredient-target-signaling pathway&quot; network of Danlou Tablets against CHD with PBS syndrome was optimized by Cytoscape software. After the target biomarkers were identified, 90 participants were enrolled for diagnostic tests, and 30 CHD patients with PBS syndrome were included in before-and-after experiment to determine the therapeutic effect of Danlou Tablets on those targets. As revealed by RNA-seq and Venn diagram analysis, 200 specific genes were identified for CHD with PBS syndrome. A total of 1 118 potential therapeutic targets of Danlou Tablets were predicted through network pharmacology. Through integrated analysis of the two gene sets, 13 key targets of Danlou Tablets in the treatment of CHD with PBS syndrome were screened out, including CSF1, AKR1C2, PDGFRB, ARG1, CNR2, ALOX15B, ALDH1A1, CTSL, PLA2G7, LAP3, AKR1C3, IGFBP3, and CA1. They were presumably the biomarkers of CHD with PBS syndrome. The ELISA test further showed that CSF1 was significantly up-regulated in the peripheral blood of CHD patients with PBS syndrome, and was significantly down-regulated after Danlou Tablets intervention. CSF1 may be a biomarker for CHD with PBS syndrome, and it is positively correlated with the severity of the disease. The diagnostic cut-off of CSF1 for CHD with PBS syndrome was 286 pg·mL~(-1).

Identification of hsa_circ_0001445 of a novel circRNA-miRNA-mRNA regulatory network as potential biomarker for coronary heart disease.

To evaluate the hsa_circ_0001445 level in peripheral blood leukocytes of patients with coronary heart disease (CHD) and its related clinical factors, and predict its circRNA-miRNA-mRNA regulatory network in CHD pathogenesis via bioinformatics analysis. Peripheral blood leukocytes were isolated from the whole blood samples of 94 CHD patients (aged 65.96 ± 9.78 years old) and 126 healthy controls (aged 60.75 ± 8.81 years old). qRT-PCR was used to quantify the expression level of circRNA and subsequently analyze its association with CHD clinical parameters. Via bioinformatics algorithm and GEO datasets, differential miRNA expression was evaluated using the Limma package. A miRNA-mRNA regulatory network was predicted by cyTargetLinker. ClusterProfiler was employed to perform functional enrichment analysis of the circRNA network to investigate its role in CHD pathogenesis. The expression of hsa_circ_0001445 in peripheral blood leukocytes of CHD patients was downregulated compared with that of healthy controls. Positive correlations were evident between hsa_circ_0001445 expression level and the levels of hemoglobin, triglycerides, high- and low-density lipoprotein cholesterol. A significant negative correlation was also found between hsa_circ_0001445 expression level and age and the neutrophil level. Low expression of hsa_circ_0001445 exhibited a discriminatory ability between CHD patients and healthy controls with a sensitivity of 67.5% and a specificity of 76.6% (p < 0.05). By bioinformatics analysis, 405 gene ontology terms were identified. The Kyoto Encyclopedia of Genes and Genomes terms focused principally on the PI3K-Akt signaling pathway. hsa_circ_0001445 was associated with the expression of three miRNAs that may regulate 18 genes involved in KEGG processes: hsa-miR-507, hsa-miR-375-3p, and hsa-miR-942-5p. The hsa_circ_0001445 level in peripheral blood leukocytes may serve as a biomarker for CHD diagnosis. Our work on circRNA-miRNA-mRNA networks suggests a potential role for hsa_circ_0001445 in CHD development.

Abstract MP23: Circulating Gut Microbiota-Related Metabolites and Risk of Coronary Heart Disease: A Prospective, Multiethnic, Metabolomic Study

Introduction: Despite the importance of gut microbiota in human cardiometabolic health, the associations between circulating levels of gut microbiota-related metabolites and incident coronary heart disease (CHD) remain largely unexplored. Hypothesis: Certain circulating microbial metabolites are associated with incident CHD. Methods: This is a multi-stage and multiethnic metabolomics study. We first conducted a global, semi-quantitative assay for discovery among 900 incident CHD cases and 900 age-/sex-/race-matched controls (300 pairs of Black Americans, White Americans, and Chinese adults, respectively) selected from the Southern Community Cohort Study and Shanghai Men’s and Women’s Health Studies. We focused on 226 metabolites that were potentially related to gut microbiota and applied conditional logistic regression to estimate odds ratios (ORs) of CHD associated with a 1-SD increase of log-transformed metabolites adjusting for traditional CHD risk factors. Then, an in-silico validation was conducted using existing metabolites data of 9,264 participants from the Multi-Ethnic Study of Atherosclerosis and Atherosclerosis Risk in Communities Study. Results: In the discovery stage, we identified 73 named microbial metabolites related to incident CHD risk with a false discovery rate&lt;0.10 or nominal p &lt;0.05 and a large effect size (ORs &gt;1.5 or &lt;0.5). These metabolites were from super pathways of amino acids (n=28), lipids (n=24), nucleotides (n=6), carbohydrates (n=4), energy (n=4), xenobiotics (n=4), and cofactors/vitamins (n=3). Of them, 61 metabolites were available for the in-silico validation, and 30 showed a significant association ( p &lt;0.05) with the same direction as the discovery results. After further adjustments for established CHD risk factors (e.g., glucose and LDL-cholesterol), 25 metabolites remained significant. A 14%-48% increased risk was observed for N-acetylglutamate (OR=1.48), sphingomyelin (1.42), imidazole propionate (1.37), hypoxanthine (1.29), guaiacol sulfate (1.28), glutamate (1.22), 2-hydroxyphenylacetate (1.20), 3-hydroxybutyrate (1.19), 3-hydroxy-2-ethylpropionate (1.17), 1-methyl-4-imidazoleacetate (1.16), urea (1.16), urate (1.16), 4-hydroxyphenylacetate (1.15), choline (1.15), isoleucine (1.14), and glycerol (1.14). Meanwhile, a significant inverse association was found for taurine (OR=0.64), asparagine (0.75), serotonin (0.78), histidine (0.79), threonine (0.81), glutamine (0.83), glycine (0.84), oxalate (0.85), and N-methylproline (0.89). Conclusions: Among ethnically and geographically diverse populations, we identified and validated some circulating gut microbiota-related metabolites as potential novel biomarkers for incident CHD. Targeted quantitative assays to confirm these results are ongoing, which are essential to inform potential clinical utility.

CircRNA, a novel diagnostic biomarker for coronary heart disease.

This study aimed to identify the potential diagnostic biomarkers of coronary heart disease (CHD) from exosome-derived circRNA. The microarray data of circRNA derived from the exosomes of patients with CHD and mRNA in acute myocardial infarction was retrieved from exoRBase website and GEO database (GSE61144), respectively, to identify the differentially expressed genes (DEGs). Our findings detected the differentially expressed circRNAs and mRNAs and predicted their correlation with microRNAs using the microRNA target prediction website, thus ascertaining the corresponding circ-microRNA and micro-mRNAs. Then, we performed systematic Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis on the differentially expressed mRNA. Protein-Protein Interactions (PPI) of these DEGs were examined using STRING. The receiver operator characteristic (ROC) curve was used to validate the diagnostic efficacy of circRNA in patients with CHD. Finally, the RNAs identified in this study were verified by quantitative real-time polymerase chain reaction (qRT-PCR). A total of 85 differentially expressed circRNAs (4 up-regulated and 81 down-regulated) were identified by screening the circRNAs in exosome of CHD patients. Based on the prediction data of circRNA, mRNA, and the corresponding microRNA, a ceRNA network was constructed, including 7 circRNA nodes, 5 microRNA nodes, and 2 mRNA nodes. Finally, validated by qRT-PCR testing, we found circRNA0001785, circRNA0000973, circRNA0001741, and circRNA0003922 to be the promising candidate for the effective prediction of CHD. These potential diagnostic markers can provide insight for further research on the occurrence of CHD or even acute coronary syndrome (ACS).

Serum metabolomic analysis revealed potential metabolite biomarkers for diabetes mellitus with coronary heart disease.

Diabetes, including its predominant form, type 2 diabetes mellitus (T2DM), has a distinctive correlation with coronary heart disease (CHD). Patients with diabetes have shown statistically higher potential risk of developing CHD complications than those without diabetes. In this study, we have conducted a metabolomic analysis of serum samples from healthy controls as well as patients with T2DM or both T2DM and CHD (CHD-T2DM). Statistical analysis of the metabolomic data revealed 611 and 420 significantly altered metabolic signatures in T2DM and CHD-T2DM patients, respectively, when compared to the healthy controls. Meanwhile, 653 metabolic features were significantly different between the CHD-T2DM and T2DM groups. Some of the metabolites at significantly different levels were identified and may serve as potential biomarkers for T2DM or CHD-T2DM. We selected three candidates, phosphocreatine (PCr), cyclic guanosine monophosphate (cGMP) and taurine for further validation among independent T2DM, CHD-T2DM and healthy control populations. These three metabolites were found to be significantly elevated in the CHD-T2DM group when compared to both T2DM and healthy control groups by the metabolomic analysis. Our results indicated that both PCr and cGMP but not taurine were successfully validated and may serve as predictive biomarkers of CHD in patients with T2DM.

4′-phosphopantetheine acts as a potential antioxidant to limit atherosclerotic plaque formation by inhibiting ROS generation

Coronary heart disease (CHD) is caused by coronary atherosclerosis and has a high morbidity and mortality rate worldwide. There are challenges in both early screening and treatment of CHD. The appearance and development of CHD is a complex metabolic disorder process. Therefore, to search for new biomarkers of CHD, we analyzed the peripheral blood metabolome in patients with CHD. In the study, a plasma metabolite, 4'-Phosphopantetheine (4-PPanSH), which was discovered by HPLC-MS/MS, as peripheral blood 4-PPanSH decreases, the degree of coronary blockage gradually aggravates. In addition, the 4-PPanSH supplement limited atherosclerotic plaque formation and endothelial injury in mice. Further, in vascular endothelial cells, 4-PPanSH effectively inhibited ROS generation and ox-LDL accumulation. In summary, 4-PPanSH was associated with the degree of coronary stenosis, and the 4-PPanSH supplement reduced atherosclerotic plaque generation, which could be associated with 4-PPanSH acting as a potent antioxidant that inhibits ROS generation and alleviates vascular endothelial injury.

Identification of DNA methylation-regulated genes as potential biomarkers for coronary heart disease via machine learning in the Framingham Heart Study

BackgroundDNA methylation-regulated genes have been demonstrated as the crucial participants in the occurrence of coronary heart disease (CHD). The machine learning based on DNA methylation-regulated genes has tremendous potential for mining non-invasive predictive biomarkers and exploring underlying new mechanisms of CHD.ResultsFirst, the 2085 age-gender-matched individuals in Framingham Heart Study (FHS) were randomly divided into training set and validation set. We then integrated methylome and transcriptome data of peripheral blood leukocytes (PBLs) from the training set to probe into the methylation and expression patterns of CHD-related genes. A total of five hub DNA methylation-regulated genes were identified in CHD through dimensionality reduction, including ATG7, BACH2, CDKN1B, DHCR24 and MPO. Subsequently, methylation and expression features of the hub DNA methylation-regulated genes were used to construct machine learning models for CHD prediction by LightGBM, XGBoost and Random Forest. The optimal model established by LightGBM exhibited favorable predictive capacity, whose AUC, sensitivity, and specificity were 0.834, 0.672, 0.864 in the validation set, respectively. Furthermore, the methylation and expression statuses of the hub genes were verified in monocytes using methylation microarray and transcriptome sequencing. The methylation statuses of ATG7, DHCR24 and MPO and the expression statuses of ATG7, BACH2 and DHCR24 in monocytes of our study population were consistent with those in PBLs from FHS.ConclusionsWe identified five DNA methylation-regulated genes based on a predictive model for CHD using machine learning, which may clue the new epigenetic mechanism for CHD.

Exercise and Escitalopram in the Treatment of Anxiety in Patients with Coronary Heart Disease: One Year Follow-Up of the UNWIND Randomized Clinical Trial.

Anxiety is common among patients with coronary heart disease (CHD) and is associated with a worse prognosis. UNWIND was a 12-week randomized clinical trial comparing exercise and escitalopram to placebo on measures of anxiety, depression, and CHD biomarkers. Primary results of the trial reported that treatment with escitalopram, but not exercise, was associated with significant reductions in anxiety and depression. At 1-year follow-up, participants completed the Hospital Anxiety-Depression Scale-Anxiety (HADS-A) along with the HADS-Depression (HADS-D), the Beck Depression Inventory-II (BDI-II), and the Godin Leisure Time Exercise survey to assess physical activity. Results showed that those patients randomized to escitalopram had lower scores on the HADS-A compared to those randomized to exercise (P = 0.006) and had less depression compared to exercise on the HADS-D (P = 0.004) and BDI-II (P = 0.004). Participants randomized to exercise reported higher levels of physical activity at 1-year compared to those randomized to Placebo (P = 0.039). However, despite reporting being more physically active, those randomized to exercise did not have less anxiety or depression compared to placebo controls. Escitalopram appears to be a safe and effective treatment for anxiety; exercise has many health benefits, but does not appear to be effective in treating anxiety.

Small Dense Low-Density Lipoprotein Cholesterol as a Novel Biomarker of Coronary Heart Disease

Objective: To compare serum small dense low-density lipoprotein cholesterol levels in coronary heart disease (CHD) patients and healthy controls.&#x0D; Study Design: Comparative cross-sectional study.&#x0D; Place and Duration of Study: Department of Chemical Pathology and Endocrinology, Armed Forces Institute of Pathology (AFIP), Rawalpindi Pakistan, in collaboration with AFIC Rawalpindi from Feb to Dec 2021.&#x0D; Methodology: A total of 220 participants were selected for the study, 120 healthy controls and 100 CHD patients. Fasting blood samples after 12 hours of fast were collected for lipid profile and small dense low-density lipoprotein cholesterol (sdLDL-C) levels. SdLDL-C levels were analyzed by automated, standardized enzymatic assay on Siemens Advia 1800 automated chemistry analyzer using Ex Denka Seiken kits.&#x0D; Results: Among the total participants, 154 (70%) were males, and 66(30%) were females. The median age of all participants was 55(IQR: 52 -56) years, while their median sdLDL-C was 0.93 (IQR: 0.56-1.08) mmol/L. Results showed that small, dense LDL cholesterol serum levels were significantly raised in CHD patients compared to healthy controls (p-value &lt;0.05).&#x0D; Conclusion: The current study showed that patients with CHD had elevated small, dense LDL-C levels compared to the healthy control group.