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Abstract Mitochondrial dysfunction and immune cell infiltration play crucial yet incompletely understood roles in the pathogenesis of calcific aortic valve disease (CAVD). This study aimed to identify immune-related mitochondrial genes critical to the pathological process of CAVD using multiomics approaches. The CIBERSORT algorithm was employed to evaluate immune cell infiltration characteristics in CAVD patients. An integrative analysis combining weighted gene coexpression network analysis (WGCNA), machine learning, and summary data-based Mendelian randomization (SMR) was performed to identify key mitochondrial genes implicated in CAVD. Spearman’s rank correlation analysis was also performed to assess the relationships between key mitochondrial genes and infiltrating immune cells. Compared with those in normal aortic valve tissue, an increased proportion of M0 macrophages and resting memory CD4 T cells, along with a decreased proportion of plasma cells and activated dendritic cells, were observed in CAVD patients. Additionally, eight key mitochondrial genes associated with CAVD, including PDK4, LDHB, SLC25A36, ALDH9A1, ECHDC2, AUH, ALDH2, and BNIP3, were identified through the integration of WGCNA and machine learning methods. Subsequent SMR analysis, incorporating multiomics data, such as expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (mQTLs), revealed a significant causal relationship between ALDH9A1 expression and a reduced risk of CAVD. Moreover, ALDH9A1 expression was inversely correlated with M0 macrophages and positively correlated with M2 macrophages. These findings suggest that increased ALDH9A1 expression is significantly associated with a reduced risk of CAVD and that it may exert its protective effects by modulating mitochondrial function and immune cell infiltration. Specifically, ALDH9A1 may contribute to the shift from M0 macrophages to anti-inflammatory M2 macrophages, potentially mitigating the pathological progression of CAVD. In conclusion, ALDH9A1 represents a promising molecular target for the diagnosis and treatment of CAVD. However, further validation through in vivo and n vitro studies is necessary to confirm its role in CAVD pathogenesis and therapeutic potential.

Abstract The role of RNA N6-methyladenosine (m6A) modification in the regulation of the immune microenvironment in ischaemic cardiomyopathy (ICM) remains largely unclear. This study first identified differential m6A regulators between ICM and healthy samples, and then systematically evaluated the effects of m6A modification on the characteristics of the immune microenvironment in ICM, including the infiltration of immune cells, the human leukocyte antigen (HLA) gene, and HALLMARKS pathways. A total of seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15 and YTHDF3, were identified using a random forest classifier. A diagnostic nomogram based on these seven key m6A regulators could effectively distinguish patients with ICM from healthy subjects. We further identified two distinct m6A modification patterns (m6A cluster-A and m6A cluster-B) that are mediated by these seven regulators. Meanwhile, we also noted that one m6A regulator, WTAP, was gradually upregulated, while the others were gradually downregulated in the m6A cluster-A vs. m6A cluster-B vs. healthy subjects. In addition, we observed that the degree of infiltration of the activated dendritic cells, macrophages, natural killer (NK) T cells, and type-17 T helper (Th17) cells gradually increased in m6A cluster-A vs. m6A cluster-B vs. healthy subjects. Furthermore, m6A regulators, including FTO, YTHDC1, YTHDF3, FMR1, ZC3H13, and RBM15 were significantly negatively correlated with the above-mentioned immune cells. Additionally, several differential HLA genes and HALLMARKS signalling pathways between the m6A cluster-A and m6A cluster-B groups were also identified. These results suggest that m6A modification plays a key role in the complexity and diversity of the immune microenvironment in ICM, and seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15, and YTHDF3, may be novel biomarkers for the accurate diagnosis of ICM. Immunotyping of patients with ICM will help to develop immunotherapy strategies with a higher level of accuracy for patients with a significant immune response.

Abstract Background The immune system plays a vital role in the pathological process of ischaemic stroke. However, the exact immune-related mechanism remains unclear. The current research aimed to identify immune-related key genes associated with ischaemic stroke. Methods CIBERSORT was utilized to reveal the immune cell infiltration pattern in ischaemic stroke patients. Meanwhile, a weighted gene coexpression network analysis (WGCNA) was utilized to identify meaningful modules significantly correlated with ischaemic stroke. The characteristic genes correlated with ischaemic stroke were identified by the following two machine learning methods: the support vector machine-recursive feature elimination (SVM-RFE) algorithm and least absolute shrinkage and selection operator (LASSO) logistic regression. Results The CIBERSORT results suggested that there was a decreased infiltration of naive CD4 T cells, CD8 T cells, resting mast cells and eosinophils and an increased infiltration of neutrophils, M0 macrophages and activated memory CD4 T cells in ischaemic stroke patients. Then, three significant modules (pink, brown and cyan) were identified to be significantly associated with ischaemic stroke. The gene enrichment analysis indicated that 519 genes in the above three modules were mainly involved in several inflammatory or immune-related signalling pathways and biological processes. Eight hub genes (ADM, ANXA3, CARD6, CPQ, SLC22A4, UBE2S, VIM and ZFP36) were revealed to be significantly correlated with ischaemic stroke by the LASSO logistic regression and SVM-RFE algorithm. The external validation combined with a RT‒qPCR analysis revealed that the expression levels of ADM, ANXA3, SLC22A4 and VIM were significantly increased in ischaemic stroke patients and that these key genes were positively associated with neutrophils and M0 macrophages and negatively correlated with CD8 T cells. The mean AUC value of ADM, ANXA3, SLC22A4 and VIM was 0.80, 0.87, 0.91 and 0.88 in the training set, 0.85, 0.77, 0.86 and 0.72 in the testing set and 0.87, 0.83, 0.88 and 0.91 in the validation samples, respectively. Conclusions These results suggest that the ADM, ANXA3, SLC22A4 and VIM genes are reliable serum markers for the diagnosis of ischaemic stroke and that immune cell infiltration plays a crucial role in the occurrence and development of ischaemic stroke.

Abstract Background The immune system plays a vital role in the pathophysiology of acute myocardial infarction (AMI). However, the exact immune related mechanism is still unclear. This research study aimed to identify key immune-related genes involved in AMI. Methods CIBERSORT, a deconvolution algorithm, was used to determine the proportions of 22 subsets of immune cells in blood samples. The weighted gene co-expression network analysis (WGCNA) was used to identify key modules that are significantly associated with AMI. Then, CIBERSORT combined with WGCNA were used to identify key immune-modules. The protein–protein interaction (PPI) network was constructed and Molecular Complex Detection (MCODE) combined with cytoHubba plugins were used to identify key immune-related genes that may play an important role in the occurrence and progression of AMI. Results The CIBERSORT results suggested that there was a decrease in the infiltration of CD8 + T cells, gamma delta (γδ) T cells, and resting mast cells, along with an increase in the infiltration of neutrophils and M0 macrophages in AMI patients. Then, two modules (midnightblue and lightyellow) that were significantly correlated with AMI were identified, and the salmon module was found to be significantly associated with memory B cells. Gene enrichment analysis indicated that the 1,171 genes included in the salmon module are mainly involved in immune-related biological processes. MCODE analysis was used to identify four different MCODE complexes in the salmon module, while four hub genes (EEF1B2, RAC2, SPI1, and ITGAM) were found to be significantly correlated with AMI. The correlation analysis between the key genes and infiltrating immune cells showed that SPI1 and ITGAM were positively associated with neutrophils and M0 macrophages, while they were negatively associated with CD8 + T cells, γδ T cells, regulatory T cells (Tregs), and resting mast cells. The RT-qPCR validation results found that the expression of the ITGAM and SPI1 genes were significantly elevated in the AMI samples compared with the samples from healthy individuals, and the ROC curve analysis showed that ITGAM and SPI1 had a high diagnostic efficiency for the recognition of AMI. Conclusions Immune cell infiltration plays a crucial role in the occurrence and development of AMI. ITGAM and SPI1 are key immune-related genes that are potential novel targets for the prevention and treatment of AMI.

BackgroundThe immune system significantly participates in the pathologic process of atrial fibrillation (AF). However, the molecular mechanisms underlying this participation are not completely explained. The current research aimed to identify critical genes and immune cells that participate in the pathologic process of AF.MethodsCIBERSORT was utilized to reveal the immune cell infiltration pattern in AF patients. Meanwhile, weighted gene coexpression network analysis (WGCNA) was utilized to identify meaningful modules that were significantly correlated with AF. The characteristic genes correlated with AF were identified by the least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithm.ResultsIn comparison to sinus rhythm (SR) individuals, we observed that fewer activated mast cells and regulatory T cells (Tregs), as well as more gamma delta T cells, resting mast cells, and M2 macrophages, were infiltrated in AF patients. Three significant modules (pink, red, and magenta) were identified to be significantly associated with AF. Gene enrichment analysis showed that all 717 genes were associated with immunity- or inflammation-related pathways and biological processes. Four hub genes (GALNT16, HTR2B, BEX2, and RAB8A) were revealed to be significantly correlated with AF by the SVM-RFE algorithm and LASSO logistic regression. qRT–PCR results suggested that compared to the SR subjects, AF patients exhibited significantly reduced BEX2 and GALNT16 expression, as well as dramatically elevated HTR2B expression. The AUC measurement showed that the diagnostic efficiency of BEX2, HTR2B, and GALNT16 in the training set was 0.836, 0.883, and 0.893, respectively, and 0.858, 0.861, and 0.915, respectively, in the validation set.ConclusionsThree novel genes, BEX2, HTR2B, and GALNT16, were identified by WGCNA combined with machine learning, which provides potential new therapeutic targets for the early diagnosis and prevention of AF.

BackgroundUpstream transcription factor 1 (USF1) single-nucleotide polymorphisms (SNPs) are significantly associated with serum lipid levels in several different ethnic groups or populations, but their association with lipid levels and the risk of early-onset coronary artery disease (EOCAD) has not been reported in Han populations of southern China.MethodsSix USF1 SNPs (rs3737787, rs2774276, rs2516839, rs2516838, rs1556259, and rs2516837) were genotyped by next-generation sequencing (NGS) techniques in 686 control subjects and 728 patients with EOCAD.ResultsThe genotypic and allelic frequencies of the USF1 rs3737787 SNP were significantly different between the control and EOCAD groups. The subgroup analysis identified that the rs3737787T allele was related to a decreased risk of EOCAD, whereas the rs3737787C–rs2774276G–rs2516839A and rs3737787C–rs2774276G–rs2516839G haplotypes were related to an increased risk of EOCAD in men, and the rs3737787C–rs2774276G–rs2516839A and rs3737787T–rs2774276C–rs2516839A haplotypes were correlated with an increased risk of EOCAD in women (p < 0.05–0.01). Male rs3737787T allele carriers had lower low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglyceride (TG) concentrations than the rs3737787T allele non-carriers (p < 0.01). The interactions of rs3737787 with alcohol consumption and rs2516839 with smoking affected serum TC and LDL-C levels in men, whereas the interaction of rs3737787 with alcohol consumption affected serum high-density lipoprotein cholesterol (HDL-C) levels and the rs2516839-smoking interaction affected serum TC levels in women (pI < 0.001). The expression levels of the USF1 mRNA, interleukin 1β (IL-1β), tumor necrosis factor-α (TNF-α), and interleukin 6 (IL-6) were significantly lower in controls than in patients with EOCAD, and rs3737787T allele carriers displayed lower IL-1β, TNF-α, IL-6, and USF1 mRNA expression levels than the rs3737787T allele non-carriers. In addition, IL-1β, TNF-α, and IL-6 expression levels were significantly positively correlated with USF1 mRNA levels (p < 0.01).ConclusionSex-specific correlations were identified between the USF1 rs3737787T allele with blood lipid levels and the risk of EOCAD. The USF1 rs3737787T allele affects the risk of EOCAD by modulating serum lipid levels and the expression of inflammatory factors, including IL-1β, TNF-α, and IL-6.

Abstract This investigation seeks to dissect coronary artery disease molecular target candidates along with its underlying molecular mechanisms. Data on patients with CAD across three separate array data sets, GSE66360, GSE19339 and GSE97320 were extracted. The gene expression profiles were obtained by normalizing and removing the differences between the three data sets, and important modules linked to coronary heart disease were identified using weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and genomes (KEGG) pathway enrichment analyses were applied in order to identify statistically significant genetic modules with the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool (version 6.8; http://david.abcc.ncifcrf.gov ). The online STRING tool was used to construct a protein–protein interaction (PPI) network, followed by the use of Molecular Complex Detection (MCODE) plug-ins in Cytoscape software to identify hub genes. Two significant modules (green-yellow and magenta) were identified in the CAD samples. Genes in the magenta module were noted to be involved in inflammatory and immune-related pathways, based on GO and KEGG enrichment analyses. After the MCODE analysis, two different MCODE complexes were identified in the magenta module, and four hub genes (ITGAM, degree = 39; CAMP, degree = 37; TYROBP, degree = 28; ICAM1, degree = 18) were uncovered to be critical players in mediating CAD. Independent verification data as well as our RT-qPCR results were highly consistent with the above finding. ITGAM, CAMP, TYROBP and ICAM1 are potential targets in CAD. The underlying mechanism may be related to the transendothelial migration of leukocytes and the immune response.

Abstract Background The current research aimed to expound the genes and pathways that are involved in coronary artery disease (CAD) and ischaemic stroke (IS) and the related mechanisms. Methods Two array CAD datasets of (GSE66360 and GSE97320) and an array IS dataset (GSE22255) were downloaded. Differentially expressed genes (DEGs) were identified using the limma package. The online tool Database for Annotation, Visualization and Integrated Discovery (DAVID) (version 6.8; david.abcc.ncifcrf.gov ) was used to annotate the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses of the DEGs. A protein-protein interaction (PPI) network was constructed by Cytoscape software, and then Molecular Complex Detection (MCODE) analysis was used to screen for hub genes. The hub genes were also confirmed by RT-qPCR and unconditional logistic regression analysis in our CAD and IS patients. Results A total of 20 common DEGs (all upregulated) were identified between the CAD/IS and control groups. Eleven molecular functions, 3 cellular components, and 49 biological processes were confirmed by GO enrichment analysis, and the 20 common upregulated DEGs were enriched in 21 KEGG pathways. A PPI network including 24 nodes and 68 edges was constructed with the STRING online tool. After MCODE analysis, the top 5 high degree genes, including Jun proto-oncogene (JUN, degree = 9), C-X-C motif chemokine ligand 8 (CXCL8, degree = 9), tumour necrosis factor (TNF, degree = 9), suppressor of cytokine signalling 3 (SOCS3, degree = 8) and TNF alpha induced protein 3 (TNFAIP3, degree = 8) were noted. RT-qPCR results demonstrated that the expression levels of CXCL8 were increased in IS patients than in normal participants and the expression levels of SOCS3, TNF and TNFAIP were higher in CAD/IS patients than in normal participants. Meanwhile, unconditional logistic regression analysis revealed that the incidence of CAD or IS was positively correlated with the CXCL8, SOCS3, TNF and TNFAIP3. Conclusions The CXCL8, TNF, SOCS3 and TNFAIP3 associated with inflammation may serve as biomarkers for the diagnosis of CAD or IS. The possible mechanisms may involve the Toll-like receptor, TNF, NF-kappa B, cytokine-cytokine receptor interactions and the NOD-like receptor signalling pathways.

Xuezhikang (XZK), an extract of Chinese red yeast rice, is recommended as an optimal choice for patients with coronary heart disease (CHD) with markedly elevated triglyceride (TG) levels. This study was designed to compare the hypotriglyceridemic effects between XZK and simvastatin. The role of apolipoprotein A5 (apoA5), a key regulator of TG metabolism and a target gene of peroxisome proliferator-activated receptor α (PPARα), was to be identified in XZK-related hypotriglyceridemic actions. For these goals, hypertriglyceridemia of rats was induced by a high-fructose diet. In order to investigate the hypotriglyceridemic effects of XZK and simvastatin on these animals based on an equivalent low-density lipoprotein cholesterol (LDL-C) lowering power, we titrated their doses (XZK 80 mg/kg/d versus simvastatin 1 mg/kg/d) according to plasma LDL-C reduction of rats. Similarly, we titrated the target doses of the two agents (XZK 500 μg/ml versus simvastatin 10 μM) according to hepatocyte LDL receptor expressions, and then compared the effects of the two agents on TG and apoA5 of hepatocytes in vitro. Our results showed that XZK (80 mg/kg/d) had higher hypotriglyceridemic performance than simvastatin (1 mg/kg/d) on these animals albeit their equivalent LDL-C lowering power. Higher plasma apoA5 levels and hepatic apoA5 expressions were observed in rats treated with XZK (80 mg/kg/d) than simvastatin (1 mg/kg/d). Further, XZK (80 mg/kg/d) contributed to higher hepatic PPARα expressions of rats than simvastatin (1 mg/kg/d). Although the two agents led to an equivalent up-regulation of LDL receptors of hepatocytes, more TG reduction and apoA5 elevation were detected in hepatocytes treated with XZK (500 μg/ml) than simvastatin (10 μM). However, PPARα knockdown eliminated the above effects of XZK on hepatocytes. Therefore, our study indicates that XZK has greater hypotriglyceridemic performance than simvastatin in the setting of an equivalent LDL-C lowering power, which is attributed to more apoA5 up-regulation by this agent via the PPARα signaling pathway.

Inflammation can be activated as a defensive response by the attack of acute coronary syndrome (ACS) for ischemic tissue injury. The aim of the present study was to investigate the impact of ACS-activated inflammation on adipokine imbalance and the effects of statins on the crosstalk between inflammation and adipokine imbalance during ACS. In this study, 586 subjects were categorized into: (1) control group; (2) SA (stable angina) group; and (3) ACS group. Circulating levels of hs-CRP, adiponectin and resistin were measured by ELISA. Furthermore, forty C57BL/6 mice were randomized into: sham, AMI, low-statin (atorvastatin, 2 mg/kg/day) and high-statin (atorvastatin, 20 mg/kg/day) group. After 3 weeks, AMI models were established by surgical coronary artery ligation. Circulating levels and adipose expressions of adiponectin and resistin were assessed in animals. Besides, we investigate the effects of atorvastatin on ox-LDL-induced adipokine imbalance in vitro. As a result, we found that ACS patients had higher hs-CRP and resistin levels and lower adiponectin levels. Our correlation analysis demonstrated hs-CRP concentrations were positively correlated with resistin but negatively with adiponectin levels in humans. Our animal findings indicated higher circulating hs-CRP and resistin levels and lower adiponectin levels in AMI mice. Atorvastatin pre-treatment dose-dependently decreased hs-CRP and resistin levels but increased adiponectin levels in mice. The consistent findings were observed about the adipose expressions of resistin and adiponectin in mice. In study in vitro, ox-LDL increased cellular resistin expressions and otherwise for adiponectin expressions, which dose-dependently reversed by the addition of atorvastatin. Therefore, our study indicates that the ACS attack activates inflammation leading to adipokine imbalance that can be ameliorated by anti-inflammation of atorvastatin.