Bioinformatics analysis of vascular RNA-seq data revealed hub genes and pathways in a novel Tibetan minipig atherosclerosis model induced by a high fat/cholesterol diet

A network pharmacology-based approach to understand the mechanism of action of anti-mycobacterial activity of Acacia nilotica: a modelling and experimental study

The rapid rise in drug-resistant tuberculosis poses a serious threat to public health and demands the discovery of new anti-mycobacterial agents. Medicinal plants are a proven potential source of bioactive compounds; however, identifying those responsible for the putative anti-mycobacterial action still remains a challenging task. In this study, we undertook a systematic network pharmacology approach to identify and evaluate anti-mycobacterial compounds from a traditional plant, Acacia nilotica, as a model system. The protein-protein interaction network revealed 17 key pathways in M. tuberculosis encompassing 40 unique druggable targets that are necessary for its growth and survival. The phytochemicals of A. nilotica were preferentially found to interfere with the cell division and cell wall biogenesis proteins, especially FtsZ and Mur. Notably, the compounds epigallocatechin, ellagic acid, chlorogenic acid, and D-pinitol were found to exhibit a potential polypharmacological effect against multiple proteins. Further, in vitro studies confirmed that the selected candidates, chlorogenic acid, and ellagic acid exhibited potent anti-mycobacterial activity (against M. smegmatis) with specific inhibition of purified M.tb FtsZ enzyme. Taken together, the present study demonstrates that network pharmacology combined with molecular docking can be utilized as an efficient approach to identify potential bioactive phytochemicals from natural products along with their mechanism of action. Hence, the compounds identified in this study can be potential lead candidates for developing novel anti-mycobacterial drugs, while the key proteins identified here can be potential drug targets.

Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms

Background

The bile acid metabolism (BAM) and fatty acid metabolism (FAM) have been implicated in Kawasaki disease (KD), but their precise mechanisms remain unclear. Identifying signature cells and genes related to BAM and FAM could offer a deeper understanding of their role in the pathogenesis of KD.

Method

We analyzed the public single-cell RNA sequencing (scRNA-seq) dataset GSE1687323 to characterize the immune cell-type landscape in KD. Gene sets related to BAM and FAM were collected from the Gene Set Enrichment Analysis (GSEA) database and previous literature. We analyzed the cellular heterogeneity of BAM and FAM at the single-cell level using R packages. Through differential expressed genes (DEG) analysis, high-dimensional Weighted Correlation Network Analysis (hdWGCNA) and machine learning algorithms, we identified signature genes associated with both BAM and FAM. The cellular expression patterns of signature genes were further validated using our own scRNA-seq dataset. Finally, quantitative real-time PCR (qRT-PCR) was performed to validate the expression levels of signature genes in KD, and Receiver Operating Characteristic (ROC) curve analysis was conducted to evaluate their diagnostic potential.

Results

Enhanced BAM and FAM were detected in monocytes and natural killer (NK) cells from KD in the public scRNA-seq dataset. Our scRNA-seq data confirmed the signature genes identified by machine learning algorithms: Vimentin (VIM) and chloride intracellular channel 1 (CLIC1) were upregulated in monocytes, while integrin subunit beta 2 (ITGB2) was elevated in NK cells of KD. qRT-PCR results also validated the bioinformatic analysis. Moreover, these genes demonstrated significant diagnostic potential. In the training dataset (GSE68004), the area under the curve (AUC) values and 95% CI were as follows: VIM: 0.914 (0.863-0.966), ITGB2: 0.958 (0.925-0.991), and CLIC1: 0.985 (0.969-1). The validation dataset (GSE73461) yielded similarly robust results, with AUC values and 95% CI: VIM: 0.872 (0.811-0.934), ITGB2: 0.861 (0.795-0.928), and CLIC1: 0.893 (0.837-0.948).

Conclusion

This study successfully identified and validated VIM and CLIC1 in monocytes, as well as ITGB2 in NK cells, as novel metabolism-related genes in KD. These findings suggest that BAM and FAM may play crucial roles in KD pathogenesis. Furthermore, these signature genes hold promising potential as diagnostic biomarkers for KD.

Using weighted gene co-expression network analysis to identify key genes related to preeclampsia

Introduction

The pathogenesis of preeclampsia remains unclear, highlighting the need for the creation of dependable biomarkers. This study aimed to pinpoint genetic risk factors linked to preeclampsia through the utilization of weighted gene co-expression network analysis (WGCNA).

Methods

A gene expression profile dataset from the placentas of patients with preeclampsia was acquired from the Gene Expression Omnibus (GEO) database and employed as a discovery cohort to construct a WGCNA network. Functional enrichment analysis, pathway analysis, and the construction of protein-protein interaction (PPI) networks were performed on core genes within these modules to pinpoint hub genes. The GSE25906 dataset was utilized as a validation cohort to evaluate the diagnostic significance of the hub genes. Immunohistochemistry assays were employed to validate the protein expression levels of these genes in placental tissues from both preeclampsia and control groups.

Results

Through WGCNA, 33 co-expression modules were identified, with 4 modules significantly associated with multiple clinical traits (≥3). Among these, 75 core genes were highlighted, predominantly enriched in pathways related to the adaptive immune response and platelet activation. Notably, TYROBP, PLEK, LCP2, HCK, and ITGAM emerged as hub genes with high PPI network scores and strong diagnostic potential, all prominently associated with immunity-related pathways. Protein expression analysis revealed that these genes were downregulated in placental tissues from preeclampsia patients compared to healthy controls.

Discussions

TYROBP, PLEK, LCP2, HCK, and ITGAM are closely linked to preeclampsia and hold promise as potential biomarkers for its diagnosis and for advancing the understanding of its pathogenesis.

Beneficial effects of human umbilical cord mesenchymal stem cell (HUCMSC) transplantation on cyclophosphamide (CTX)-induced premature ovarian failure (POF) in Tibetan miniature pigs

BACKGROUND

Premature ovarian failure (POF), also known as primary ovarian insufficiency, is a common endocrine disease in young women. The emergence of regenerative medicine using stem cells may improve ovarian function and structure, and represents a promising prospect for POF treatment. In his study, we explored the therapeutic effects of human umbilical cord mesenchymal stem cell (HUCMSC) transplantation in a Tibetan miniature pig model of cyclophosphamide (CTX)-induced POF.

METHODS

We cultured and identified HUCMSCs, labeled them with DiR iodide red dye, and implanted them into a CTX-induced model of POF in Tibetan miniature pigs. The daily weight changes were recorded, and the levels of estradiol (E2) and follicle-stimulating hormone (FSH) were measured on days 0, 7, and 14. At the end of the 21-day observation period, in vivo imaging of the bilateral ovaries was performed, and the ovarian index was measured. Ovarian tissue morphology and follicles were examined by hematoxylin-eosin staining. The terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling assay was employed to assess cell apoptosis, and immunohistochemistry was used to determine the levels of p-AKT, p-ERK1/2, BAX, and BCL2 expression.

RESULTS

Our analysis indicated successful delivery of HUCMSCs to the ovaries of the POF pig model. Significant increases were observed in body weight, E2 levels, ovarian index, and number of normal follicles (all p < 0.05). Moreover, FSH levels reduced and ovarian tissue morphology improved following HUCMSCs transplantation (all p < 0.05). Importantly, upregulated p-AKT, p-ERK1/2, and BCL2 expression were observed, whereas the expression of BAX was suppressed (all p < 0.05), suggesting the inhibition of ovarian cell apoptosis.

CONCLUSION

Our study highlights the significant therapeutic effects of HUCMSC transplantation on CTX-induced POF in a Tibetan miniature pig model.

Exploring the pathogenesis of chronic atrophic gastritis with atherosclerosis via microarray data analysis

Although several studies have reported a link between chronic atrophic gastritis (CAG) and atherosclerosis, the underlying mechanisms have not been elucidated. The present study aimed to investigate the molecular mechanisms common to both diseases from a bioinformatics perspective. Gene expression profiles were obtained from the Gene Expression Omnibus database. Data on atherosclerosis and CAG were downloaded from the GSE28829 and GSE60662 datasets, respectively. We identified the differentially expressed genes co-expressed in CAG and atherosclerosis before subsequent analyses. We constructed and identified the hub genes and performed functional annotation. Finally, the transcription factor (TF)-target genes regulatory network was constructed. In addition, we validated core genes and certain TFs. We identified 116 common differentially expressed genes after analyzing the 2 datasets (GSE60662 and GSE28829). Functional analysis highlighted the significant contribution of immune responses and the positive regulation of tumor necrosis factor production and T cells. In addition, phagosomes, leukocyte transendothelial migration, and cell adhesion molecules strongly correlated with both diseases. Furthermore, 16 essential hub genes were selected with cytoHubba, including PTPRC, TYROBP, ITGB2, LCP2, ITGAM, FCGR3A, CSF1R, IRF8, C1QB, TLR2, IL10RA, ITGAX, CYBB, LAPTM5, CD53, CCL4, and LY86. Finally, we searched for key gene-related TFs, especially SPI1. Our findings reveal a shared pathogenesis between CAG and atherosclerosis. Such joint pathways and hub genes provide new insights for further studies.

Comprehensive analysis identifies crucial genes associated with immune cells mediating progression of carotid atherosclerotic plaque

BACKGROUNDS

Carotid atherosclerosis is prone to rupture and cause ischemic stroke in advanced stages of development. Our research aims to provide markers for the progression of atherosclerosis and potential targets for its treatment.

METHODS

We performed a thorough analysis using various techniques including DEGs, GO/KEGG, xCell, WGCNA, GSEA, and other methods. The gene expression omnibus datasets GSE28829 and GSE43292 were utilized for this comprehensive analysis. The validation datasets employed in this study consisted of GSE41571 and GSE120521 datasets. Finally, we validated PLEK by immunohistochemistry staining in clinical samples.

RESULTS

Using the WGCNA technique, we discovered 636 differentially expressed genes (DEGs) and obtained 12 co-expression modules. Additionally, we discovered two modules that were specifically associated with atherosclerotic plaque. A total of 330 genes that were both present in DEGs and WGCNA results were used to create a protein-protein network in Cytoscape. We used four different algorithms to get the top 10 genes and finally got 6 overlapped genes (TYROBP, ITGB2, ITGAM, PLEK, LCP2, CD86), which are identified by GSE41571 and GSE120521 datasets. Interestingly, the area under curves (AUC) of PLEK is 0.833. Besides, we found PLEK is strongly positively correlated with most lymphocytes and myeloid cells, especially monocytes and macrophages, and negatively correlated with most stromal cells (e.g, neurons, myocytes, and fibroblasts). The expression of PLEK were consistent with the immunohistochemistry results.

CONCLUSIONS

Six genes (TYROBP, ITGB2, ITGAM, PLEK, LCP2, CD86) were found to be connected with carotid atherosclerotic plaques and PLEK may be an important biomarker and a potential therapeutic target.

Identifying Oxidative Stress-Related Genes (OSRGs) as Potential Target for Treating Periodontitis Based on Bioinformatics Analysis

BACKGROUND

Periodontitis (PD) is a multifactorial inflammatory disease that is closely associated with periodontopathic bacteria. Numerous studies have demonstrated oxidative stress (OS) contributes to inflammation and is a prime factor in the development of PD. It is imperative to explore the function of newly discovered hub genes associated with OS in the advancement of PD, thereby identifying potential targets for therapeutic intervention.

OBJECTIVES

The goal of the current study was to identify the oxidative-stress-related genes (OSRGs) associated with periodontitis (PD) development using an integrated bioinformatics method.

METHODS

DEGs from GEO gene-expression data were identified using the "limma" package. We obtained OSRGs from GeneCards and utilized a Venn diagram to uncover differentially expressed OSRGs (DEOSRGs). After receiving the DEOSRGs, we employed Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analytical tools to examine their possible functions and pathways in PD. Receiver operating characteristic (ROC) curves screened for hub genes of PD. RT-qPCR and western blot analysis were used to detect DEOSRG expression in mouse ligature-induced periodontitis gingival tissues.

RESULTS

The investigation identified 273 OSRGs. Based on PPI analysis, we recognized 20 OSRGs as hub genes. GO and KEGG enrichment analysis indicated that these hub genes were predominantly enriched in leukocyte migration, lymphocyte proliferation, and humoral immune response, and associated with leukocyte trans-endothelial migration, cytokine-cytokine receptor interaction, and NF-κB signaling pathway. Following ROC analysis, VCAM1, ITGAM, FCGR3A, IL1A, PECAM1, and VCAM1were identified as PD prognostic gene. RT-qPCR and western blot analyses confirmed that the expression ITGAM, FCGR3A, and PECAM1 were significantly elevated in the gingival tissues obtained from mice.

CONCLUSION

This investigation revealed that ITGAM, FCGR3A, and PECAM1 may have a crucial function in the advancement of PD.

Gene coexpression network analysis reveals perirenal adipose tissue as an important target of prenatal malnutrition in sheep

We have previously demonstrated that pre- and early postnatal malnutrition in sheep induced depot- and sex-specific changes in adipose morphological features, metabolic outcomes, and transcriptome in adulthood, with perirenal (PER) as the major target followed by subcutaneous (SUB) adipose tissue. We aimed to identify coexpressed and hub genes in SUB and PER to identify the underlying molecular mechanisms contributing to the early nutritional programming of adipose-related phenotypic outcomes. Transcriptomes of SUB and PER of male and female adult sheep with different pre- and early postnatal nutrition histories were used to construct networks of coexpressed genes likely to be functionally associated with pre- and early postnatal nutrition histories and phenotypic traits using weighted gene coexpression network analysis. The modules from PER showed enrichment of cell cycle regulation, gene expression, transmembrane transport, and metabolic processes associated with both sexes' prenatal nutrition. In SUB (only males), a module of enriched adenosine diphosphate metabolism and development correlated with prenatal nutrition. Sex-specific module enrichments were found in PER, such as chromatin modification in the male network but histone modification and mitochondria- and oxidative phosphorylation-related functions in the female network. These sex-specific modules correlated with prenatal nutrition and adipocyte size distribution patterns. Our results point to PER as a primary target of prenatal malnutrition compared to SUB, which played only a minor role. The prenatal programming of gene expression and cell cycle, potentially through epigenetic modifications, might be underlying mechanisms responsible for observed changes in PER expandability and adipocyte-size distribution patterns in adulthood in both sexes.

Uncovering the shared molecule and mechanism between ulcerative colitis and atherosclerosis: an integrative genomic analysis

Background

Ulcerative colitis (UC) and atherosclerosis (AS) are closely related. However, the pathologic mechanisms underlying the co-occurrence of UC and AS are not well understood.

Objects

To reveal the hub molecule and mechanism involved in the co-occurrence of UC and AS.

Methods

Differentially expressed genes (DEGs) of UC and AS were obtained, and the shared DEGs of UC and AS were explored for biological function. Next, the hub genes were explored using the cytoHubba plugin. The predictive ability of the hub genes was measured by constructing the receiver operating characteristic curve. Analyses of immune infiltration and the single-gene gene set enrichment analysis (GSEA) for the hub genes were further carried out.

Results

Identification of 59 DEGs (55 were upregulated and four were downregulated) shared by both UC and AS was performed. Enriched pathways of the shared DEGs were mainly related to immunity and inflammation. Protein tyrosine phosphatase, receptor type, C (PTPRC) was identified as the hub crosstalk gene for the comorbidity of UC and AS. The upregulation of PTPRC was correlated with mast cells resting, T cells CD4 memory resting, macrophages M0, and macrophages M1. Pathways of immune and inflammatory processes, including NF-kappa B, viral protein interaction with cytokine and cytokine receptor, and cytokine-cytokine receptor interaction, were significantly correlated with high expression of PTPRC in UC and AS.

Conclusion

At the transcriptional level, our study reveals that imbalanced inflammatory and immune responses are the key pathological mechanisms underlying the comorbidity of UC and AS and that PTPRC is a key biomarker for the comorbidity of UC and AS.

Transcriptome Profiling of Different Developmental Stages on Longissimus Dorsi to Identify Genes Underlying Intramuscular Fat Content in Wannanhua Pigs

Intramuscular fat (IMF) is a key index to measure the tenderness and flavor of pork. Wannanhua pig, a famous indigenous pig breed in Anhui Province, is renowned for its high lipid deposition and high genetic divergence, making it an ideal model for investigating the lipid position trait mechanisms in pigs. However, the regulatory mechanisms of lipid deposition and development in pigs remain unclear. Furthermore, the temporal differences in gene regulation are based on muscle growth and IMF deposition. The purpose of this study was to study the expression changes of longissimus dorsi (LD) at different growth stages of WH pigs at the molecular level, to screen the candidate genes and signaling pathways related to IMF during development by transcriptome sequencing technology, and to explore the transcriptional regulation mechanism of IMF deposition-related genes at different development stages. In total, 616, 485, and 1487 genes were differentially expressed between LD60 and LD120, LD120 and LD240, and LD60 and LD240, respectively. Numerous differentially expressed genes (DEGs) associated with lipid metabolism and muscle development were identified, and most of them were involved in IMF deposition and were significantly up-regulated in LD120 and LD240 compared to LD60. STEM (Short Time-series Expression Miner) analysis indicated significant variations in the mRNA expression across distinct muscle development stages. The differential expression of 12 selected DEGs was confirmed by RT-qPCR. The results of this study contribute to our understanding of the molecular mechanism of IMF deposition and provide a new way to accelerate the genetic improvement of pork quality.

Bioinformatic identification of potential biomarkers and therapeutic targets in carotid atherosclerosis and vascular dementia

Background

Vascular disease is the second most common cause of dementia. The prevalence of vascular dementia (VaD) has increased over the past decade. However, there are no licensed treatments for this disease. Carotid atherosclerosis (CAS) is highly prevalent and is the main cause of ischemic stroke and VaD. We studied co-expressed genes to understand the relationships between CAS and VaD and further reveal the potential biomarkers and therapeutic targets of CAS and VaD.

Methods

CAS and VaD differentially expressed genes (DEGs) were identified through bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE43292 and GSE122063, respectively. Furthermore, a variety of target prediction methods and network analysis approaches were used to assess the protein-protein interaction (PPI) networks, the Gene Ontology (GO) terms, and the pathway enrichment for DEGs, and the top 7 hub genes, coupled with corresponding predicted miRNAs involved in CAS and VaD, were assessed as well.

Result

A total of 60 upregulated DEGs and 159 downregulated DEGs were identified, of which the top 7 hub genes with a high degree of connectivity were selected. Overexpression of these hub genes was associated with CAS and VaD. Finally, the top 7 hub genes were coupled with corresponding predicted miRNAs. hsa-miR-567 and hsa-miR-4652-5p may be significantly associated with CAS and VaD.

Epigenetic BET reader inhibitor apabetalone (RVX-208) counters proinflammatory aortic gene expression in a diet induced obesity mouse model and in human endothelial cells

BACKGROUND AND AIMS

Obese patients are at risk for type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). A lipid-rich diet promotes arterial changes by inducing hypertension, oxidative stress, and inflammation. Bromodomain and extraterminal (BET) proteins contribute to endothelial and immune cell activation in vitro and in atherosclerosis mouse models. We aim to determine if BET inhibition can reduce lipid-rich diet-induced vascular inflammation in mice.

METHODS

Body weight, serum glucose and lipid levels were measured in mice fed a high-fat diet (HFD) or low-fat diet (LFD) for 6 weeks and at study termination. BET inhibitors apabetalone and JQ1 were co-administered with the HFD for additional 16 weeks. Aortic gene expression was analyzed post necropsy by PCR, Nanostring nCounter® Inflammation Panel and bioinformatics pathway analysis. Transcription changes and BRD4 chromatin occupancy were analyzed in primary human endothelial cells in response to TNFα and apabetalone.

RESULTS

HFD induced weight gain, visceral obesity, high fasting blood glucose, glucose intolerance and insulin resistance compared to LFD controls. HFD upregulated the aortic expression of 47 genes involved in inflammation, innate immunity, cytoskeleton and complement pathways. Apabetalone and JQ1 treatment reduced HFD-induced aortic expression of proinflammatory genes. Congruently, bioinformatics predicted enhanced signaling by TNFα in the HFD versus LFD aorta, which was countered by BETi treatment. TNFα-stimulated human endothelial cells had increased expression of HFD-sensitive genes and higher BRD4 chromatin occupancy, which was countered by apabetalone treatment.

CONCLUSIONS

HFD induces vascular inflammation in mice through TNFα signaling. Apabetalone treatment reduces this proinflammatory phenotype, providing mechanistic insight into how BET inhibitors may reduce CVD risk in obese patients.

Identification of co-expressed central genes and transcription factors in atherosclerosis-related intracranial aneurysm

Background

Numerous clinical studies have shown that atherosclerosis is one of the risk factors for intracranial aneurysms. Calcifications in the intracranial aneurysm walls are frequently correlated with atherosclerosis. However, the pathogenesis of atherosclerosis-related intracranial aneurysms remains unclear. This study aims to investigate this mechanism.

Methods

The Gene Expression Omnibus (GEO) database was used to download the gene expression profiles for atherosclerosis (GSE100927) and intracranial aneurysms (GSE75436). Following the identification of the common differentially expressed genes (DEGs) of atherosclerosis and intracranial aneurysm, the network creation of protein interactions, functional annotation, the identification of hub genes, and co-expression analysis were conducted. Thereafter, we predicted the transcription factors (TF) of hub genes and verified their expressions.

Results

A total of 270 common (62 downregulated and 208 upregulated) DEGs were identified for subsequent analysis. Functional analyses highlighted the significant role of phagocytosis, cytotoxicity, and T-cell receptor signaling pathways in this disease progression. Eight hub genes were identified and verified, namely, CCR5, FCGR3A, IL10RA, ITGAX, LCP2, PTPRC, TLR2, and TYROBP. Two TFs were also predicted and verified, which were IKZF1 and SPI1.

Conclusion

Intracranial aneurysms are correlated with atherosclerosis. We identified several hub genes for atherosclerosis-related intracranial aneurysms and explored the underlying pathogenesis. These discoveries may provide new insights for future experiments and clinical practice.

Grapefruit Juice Flavanones Modulate the Expression of Genes Regulating Inflammation, Cell Interactions and Vascular Function in Peripheral Blood Mononuclear Cells of Postmenopausal Women

Grapefruit is a rich source of flavanones, phytochemicals suggested excreting vasculoprotective effects. We previously showed that flavanones in grapefruit juice (GFJ) reduced postmenopausal women’s pulse-wave velocity (PWV), a measure of arterial stiffness. However, mechanisms of flavanone action in humans are largely unknown. This study aimed to decipher molecular mechanisms of flavanones by multi-omics analysis in PBMCs of volunteers consuming GFJ and flavanone-free control drink for 6 months. Modulated genes and microRNAs (miRNAs) were identified using microarrays. Bioinformatics analyses assessed their functions, interactions and correlations with previously observed changes in PWV. GFJ modified gene and miRNA expressions. Integrated analysis of modulated genes and miRNA-target genes suggests regulation of inflammation, immune response, cell interaction and mobility. Bioinformatics identified putative mediators of the observed nutrigenomic effect (STAT3, NF-κB) and molecular docking demonstrated potential binding of flavanone metabolites to transcription factors and cell-signaling proteins. We also observed 34 significant correlations between changes in gene expression and PWV. Moreover, global gene expression was negatively correlated with gene expression profiles in arterial stiffness and hypertension. This study revealed molecular mechanisms underlying vasculoprotective effects of flavanones, including interactions with transcription factors and gene and miRNA expression changes that inversely correlate with gene expression profiles associated with cardiovascular risk factors.

Identification of key differential genes in intimal hyperplasia induced by left carotid artery ligation

Background

Intimal hyperplasia is a common pathological process of restenosis following angioplasty, atherosclerosis, pulmonary hypertension, vein graft stenosis, and other proliferative diseases. This study aims to screen for potential novel gene targets and mechanisms related to vascular intimal hyperplasia through an integrated microarray analysis of the Gene Expression Omnibus Database (GEO) database.

Material and Methods

The gene expression profile of the GSE56143 dataset was downloaded from the Gene Expression Omnibus database. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, and the transcription factor (TF)-target gene regulatory network were used to reveal the biological functions of differential genes (DEGs). Furthermore, the expression levels of the top 10 key DEGs were verified at the mRNA and protein level in the carotid artery 7 days after ligation.

Results

A total of 373 DEGs (199 upregulated DEGs and 174 downregulated DEGs) were screened. These DEGs were significantly enriched in biological processes, including immune system process, cell adhesion, and several pathways, which were mainly associated with cell adhesion molecules and the regulation of the actin cytoskeleton. The top 10 key DEGs (Ptprc, Fn1, Tyrobp, Emr1, Itgb2, Itgax, CD44, Ctss, Ly86, and Aif1) acted as key genes in the PPI network. The verification of these key DEGs at the mRNA and protein levels was consistent with the results of the above-mentioned bioinformatics analysis.

Conclusion

The present study identified key genes and pathways involved in intimal hyperplasia induced by carotid artery ligation. These results improved our understanding of the mechanisms underlying the development of intimal hyperplasia and provided candidate targets.

Analysis of Immune and Inflammation Characteristics of Atherosclerosis from Different Sample Sources

Background

Atherosclerosis is the predominant cause of cardiovascular diseases. Existing studies suggest that the development of atherosclerosis is closely related to inflammation and immunity, but whether there are differences and similarities between atherosclerosis occurring at different sites is still unknown. We elucidated the pathological characteristics of peripheral vascular diseases by using bioinformatic analyses on immune cells and inflammation-related gene expression in atherosclerotic arteries and plaques.

Methods

Eight data sets regarding atherosclerosis were downloaded from the Gene Expression Omnibus database. Human immune genes were obtained from the IMMPORT website. The samples were scored and divided into high- and low-immune groups. Then the samples were analysed using weighted gene co-expression network analysis, while the modules were analysed using functional enrichment. The protein–protein interaction network was constructed using the STRING and Cytoscape databases. The hub immune genes were screened, and the correlation between hub immune genes and immune cells was analysed.

Results

Immune cells and their functions were significantly different during atherosclerosis development. The infiltration proportion of immune cells was approximately similar in samples from different sources of patients with carotid atherosclerosis. However, the sensitivity of lower extremity atherosclerosis samples to immune cells is lower than that of carotid atherosclerosis samples.The samples from the plaque and artery were mainly infiltrated by macrophages, T cells and mast cells. After immune cells were assessed, resting NK cells, activated mast cells and M0 macrophages were found to be key immune cells in atherosclerosis and plaque formation. In addition, CCL4, TLR2, IL1B and PTPRC were considered to be immune marker genes in atherosclerosis development. Conclusion. Bioinformatic data analysis confirms the essential role of immune cells in cardiovascular diseases, and also indicates some differences of immune and inflammation characteristics of atherosclerosis between carotid and lower extremity arteries.

Identification of hub genes and transcription factors in patients with rheumatoid arthritis complicated with atherosclerosis

The aim of this study was to explore the overlapping key genes, pathway networks and transcription factors (TFs) related to the pathogenesis of rheumatoid arthritis (RA) and atherosclerosis. The gene expression profiles of RA and atherosclerosis were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between RA and atherosclerosis were identified. The biological roles of common DEGs were explored through enrichment analysis. Hub genes were identified using protein–protein interaction networks. TFs were predicted using Transcriptional Regulatory Relationships Unraveled by Sentence Based Text Mining (TRRUST) database. The hub genes and TFs were validated with other datasets. The networks between TFs and hub genes were constructed by CytoScape software. A total of 131 DEGs (all upregulated) were identified. Functional enrichment analyses indicated that DEGs were mostly enriched in leukocyte migration, neutrophil activation, and phagocytosis. CytoScape demonstrated 12 hub genes and one gene cluster module. Four of the 12 hub genes (CSF1R, CD86, PTPRC, and CD53) were validated by other datasets. TRRUST predicted two TFs, including Spi-1 proto-oncogene (SPI1) and RUNX family transcription factor 1(RUNX1). The expression of RUNX1 was validated with another dataset. Our study explored the common pathogenesis of RA and atherosclerosis. These results may guide future experimental research and clinical transformation.

Identification of Molecular Signatures and Candidate Drugs in Vascular Dementia by Bioinformatics Analyses

Vascular dementia (VaD) is considered to be the second most common form of dementia after Alzheimer’s disease, and no specific drugs have been approved for VaD treatment. We aimed to identify shared transcriptomic signatures between the frontal cortex and temporal cortex in VaD by bioinformatics analyses. Gene ontology and pathway enrichment analyses, protein–protein interaction (PPI) and hub gene identification, hub gene–transcription factor interaction, hub gene–microRNA interaction, and hub gene–drug interaction analyses were performed. We identified 159 overlapping differentially expressed genes (DEGs) between the frontal cortex and temporal cortex that were enriched mainly in inflammation and innate immunity, synapse pruning, regeneration, positive regulation of angiogenesis, response to nutrient levels, and positive regulation of the digestive system process. We identified 10 hub genes in the PPI network (GNG13, CD163, C1QA, TLR2, SST, C1QB, ITGB2, CCR5, CRH, and TAC1), four central regulatory transcription factors (FOXC1, CREB1, GATA2, and HINFP), and four microRNAs (miR-27a-3p, miR-146a-5p, miR-335-5p, and miR-129-2-3p). Hub gene–drug interaction analysis found four drugs (maraviroc, cenicriviroc, PF-04634817, and efalizumab) that could be potential drugs for VaD treatment. Together, our results may contribute to understanding the underlying mechanisms in VaD and provide potential targets and drugs for therapeutic intervention.

Identification of novel genetic biomarkers and treatment targets for arteriosclerosis-related abdominal aortic aneurysm using bioinformatic tools

A large number of epidemiological studies have confirmed that arteriosclerosis (AS) is a risk factor for abdominal aortic aneurysm (AAA). However, the relationship between AS and AAA remains controversial. The objective of this work is to better understand the association between the two diseases by identifying the co-differentially expressed genes under both pathological conditions, so as to identify potential genetic biomarkers and treatment targets for atherosclerosis-related aneurysms. Differentially-expressed genes (DEGs) shared by both AS and AAA patients were identified by bioinformatics analyses of Gene Expression Omnibus (GEO) datasets GSE100927 and GSE7084. These DEGs were then subjected to bioinformatic analyses of protein-protein interaction (PPI), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, the identified hub genes were further validated by qRT-PCR in AS (n = 4), AAA (n = 4), and healthy (n = 4) individuals. Differential expression analysis revealed a total of 169 and 37 genes that had increased and decreased expression levels, respectively, in both AS and AAA patients compared with healthy controls. The construction of a PPI network and key modules resulted in the identification of five hub genes (SPI1, TYROBP, TLR2, FCER1G, and MMP9) as candidate diagnostic biomarkers and treatment targets for patients with AS-related AAA. AS and AAA are indeed correlated; SPI1, TYROBP, TLR2, FCER1G and MMP9 genes are potential new genetic biomarkers for AS-related AAA.

Dynamic transcriptome profiles of postnatal porcine skeletal muscle growth and development

BACKGROUND

Skeletal muscle growth and development are closely associated with the quantity and quality of pork production. We performed a transcriptomic analysis of 12 Longissimus dorsi muscle samples from Tibetan piglets at four postnatal stages of 0, 14, 30, and 60 days using RNA sequencing.

RESULTS

According to the pairwise comparisons between the libraries of the muscle samples at the four postnatal stages, a total of 4115 differentially expressed genes (DEGs) were identified in terms of |log2(fold change)| ≥ 1 and an adjusted P value < 0.01. Short-time series expression miner (STEM) analysis of the DEGs identified eight significantly different expression profiles, which were divided into two clusters based on the expression pattern. DEGs in cluster I displayed a pattern of decreasing to a nadir, and then a rise, and the significantly enriched gene ontology (GO) terms detected using them were involved in multiple processes, of which the cell cycle, immunocyte activation and proliferation, as well as actin cytoskeleton organization, were the top three overrepresented processes based on the GO terms functional classification. DEGs in cluster II displayed a pattern of increasing to a peak, then declining, which mainly contributed to protein metabolism. Furthermore, besides the pathways related to immune system, a few diseases, and protein metabolism, the DEGs in clusters I and II were significantly enriched in pathways related to muscle growth and development, such as the Rap1, PI3K-Akt, AMPK, and mTOR signaling pathways.

CONCLUSIONS

This study revealed GO terms and pathways that could affect the postnatal muscle growth and development in piglets. In addition, this study provides crucial information concerning the molecular mechanisms of muscle growth and development as well as an overview of the piglet transcriptome dynamics throughout the postnatal period in terms of growth and development.

Distinct peripheral blood monocyte and neutrophil transcriptional programs following intracerebral hemorrhage and different etiologies of ischemic stroke

Understanding cell-specific transcriptome responses following intracerebral hemorrhage (ICH) and ischemic stroke (IS) will improve knowledge of the immune response to brain injury. Transcriptomic profiles of 141 samples from 48 subjects with ICH, different IS etiologies, and vascular risk factor controls were characterized using RNA-seq in isolated neutrophils, monocytes and whole blood. In both IS and ICH, monocyte genes were down-regulated, whereas neutrophil gene expression changes were generally up-regulated. The monocyte down-regulated response to ICH included innate, adaptive immune, dendritic, NK cell and atherosclerosis signaling. Neutrophil responses to ICH included tRNA charging, mitochondrial dysfunction, and ER stress pathways. Common monocyte and neutrophil responses to ICH included interferon signaling, neuroinflammation, death receptor signaling, and NFAT pathways. Suppressed monocyte responses to IS included interferon and dendritic cell maturation signaling, phagosome formation, and IL-15 signaling. Activated neutrophil responses to IS included oxidative phosphorylation, mTOR, BMP, growth factor signaling, and calpain proteases-mediated blood-brain barrier (BBB) dysfunction. Common monocyte and neutrophil responses to IS included JAK1, JAK3, STAT3, and thrombopoietin signaling. Cell-type and cause-specific approaches will assist the search for future IS and ICH biomarkers and treatments.

Novel Insights into the Potential Diagnostic Value of Circulating Exosomal IncRNA-Related Networks in Large Artery Atherosclerotic Stroke

Exosomes show diagnostic and therapeutic promise as carriers of ncRNAs in diseases. LncRNAs in exosomes have been identified as being stable and avoided degradation by nucleolytic enzymes. Although lncRNAs have been confirmed to be important in cancers, no studies for exo-lncRNAs have been reported in LAA stroke. High-throughput sequencing was performed to detect the differential expression profiles of lncRNAs in five paired plasma-derived exosome samples from patients with LAA stroke and controls (matched on vascular risk factors). Exo-lncRNA-associated networks were predicted with a combination of multiple databases. The expression of the selected genes in the networks was confirmed by qRT-PCR in a validation set (LAA vs. controls = 30:30). Furthermore, ROC analysis was used to evaluate the diagnostic performance of the lncRNA-related networks. A total of 1,020 differentially expressed lncRNAs were identified in LAA stroke patients. GO and KEGG pathway analyses indicated that their target genes are involved in atherosclerosis-related pathways, including inflammation, cell adhesion, and cell migration. qRT-PCR confirmed that the expression trend of differential expressed genes was consistent with RNA-seq. Furthermore, the AUCs of the lnc_002015-related network and lnc_001350-related network were 0.959 and 0.97, respectively, in LAA stroke. Our study showed the differential expression of lncRNAs in plasma exosomes and presented related diagnostic networks for LAA stroke for the first time. The results suggested that exosomal lncRNA-related networks could be potential diagnostic tools in LAA stroke.

Identification of key pathways and genes in carotid atherosclerosis through bioinformatics analysis of RNA-seq data

While acknowledging carotid atherosclerosis (CAS) as a risk factor for ischemic stroke, reports on its pathogenesis are scarce. This study aimed to explore the potential mechanism of CAS through RNA-seq data analysis. Carotid intima tissue samples from CAS patients and healthy subjects were subjected to RNA-seq analysis, which yielded, 1,427 differentially expressed genes (DEGs) related to CAS. Further, enrichment analysis (Gene Ontology, KEGG pathway, and MOCDE analysis) was performed on the DEGs. Hub genes identified via the protein-protein interaction network (PPI) were then analyzed using TRRUST, DisGeNET, PaGenBase, and CMAP databases. Results implicated inflammation and immunity in the pathogenesis of CAS. Also, lung disease was associated with CAS. Hub genes were expressed in multiple diseases, mainly regulated by RELA and NFKB1. Moreover, three small-molecule compounds were found via the CMAP database for management of CAS; hub genes served as potential targets. Collectively, inflammation and immunity are the potential pathological mechanisms of CAS. This study implicates CeForanide, Chenodeoxycholic acid, and 0317956-0000 as potential drug candidates for CAS treatment.

Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease

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.