Regulatory T Cell-Related Gene Biomarkers in the Deterioration of Atherosclerosis

CETP-derived Peptide Seq-1, the Key Component of HB-ATV-8 Vaccine Prevents Stress Responses, and Promotes Downregulation of Pro-Fibrotic Genes in Hepatocytes and Stellate Cells

BACKGROUND

The nasal vaccine HB-ATV-8 has emerged as a promising approach for NAFLD (non-alcoholic fatty liver disease) and atherosclerosis prevention. HB-ATV-8 contains peptide seq-1 derived from the carboxy-end of the Cholesteryl Ester Transfer Protein (CETP), shown to reduce liver fibrosis, inflammation, and atherosclerotic plaque formation in animal models. Beyond the fact that this vaccine induces B-cell lymphocytes to code for antibodies against the seq-1 sequence, inhibiting CETP's cholesterol transfer activity, we have hypothesized that beyond the modulation of CETP activity carried out by neutralizing antibodies, the observed molecular effects may also correspond to the direct action of peptide seq-1 on diverse cellular systems and molecular features involved in the development of liver fibrosis.

METHODS

The HepG2 hepatoma-derived cell line was employed to establish an in vitro steatosis model. To obtain a conditioned cell medium to be used with hepatic stellate cell (HSC) cultures, HepG2 cells were exposed to fatty acids or fatty acids plus peptide seq-1, and the culture medium was collected. Gene regulation of COL1A1, ACTA2, TGF-β, and the expression of proteins COL1A1, MMP-2, and TIMP-2 were studied.

AIM

To establish an in vitro steatosis model employing HepG2 cells that mimics molecular processes observed in vivo during the onset of liver fibrosis. To evaluate the effect of peptide Seq-1 on lipid accumulation and pro-fibrotic responses. To study the effect of Seq-1-treated steatotic HepG2 cell supernatants on lipid accumulation, oxidative stress, and pro-fibrotic responses in HSC.

RESULTS AND CONCLUSION

Peptide seq-1-treated HepG2 cells show a downregulation of COLIA1, ACTA2, and TGF-β genes, and a decreased expression of proteins such as COL1A1, MMP-2, and TIMP-2, associated with the remodeling of extracellular matrix components. The same results are observed when HSCs are incubated with peptide Seq-1-treated steatotic HepG2 cell supernatants. The present study consolidates the nasal vaccine HB-ATV-8 as a new prospect in the treatment of NASH directly associated with the development of cardiovascular disease.

Single-cell and transcriptomic analyses reveal the influence of diabetes on ovarian cancer

BACKGROUND

There has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.

METHODS

Multiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.

RESULTS

The immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.

CONCLUSION

This study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

The Impact of Juvenile Microglia Transcriptomics on the Adult Brain Regeneration after Cerebral Ischemia

Microglial cells play a pivotal role in the brain's health and operation through all stages of life and in the face of illness. The contributions of microglia during the developmental phase of the brain markedly contrast with their contributions in the brain of adults after injury. Enhancing our understanding of the pathological mechanisms that involve microglial activity in brains as they age and in cerebrovascular conditions is crucial for informing the creation of novel therapeutic approaches. In this work we provide results on microglia transcriptomics in the juvenile vs injured adult brain and its impact on adult brain regeneration after cerebral ischemia. During fetal brain development, microglia cells are involved in gliogenesis, angiogenesis, axonal outgrowth, synaptogenesis, neurogenesis and synaptic reorganization by engulfing neuronal extensions. Within the mature, intact brain, microglial cells exhibit reduced movement of their processes in response to minimal neuronal activity, while they continuously monitor their surroundings and clear away cellular debris. Following a stroke in the adult brain, inflammation, neurodegeneration, or disruptions in neural equilibrium trigger alterations in both the genetic blueprint and the structure and roles of microglia, a state often described as "activated" microglia. Such genetic shifts include a notable increase in the pathways related to phagosomes, lysosomes, and the presentation of antigens, coupled with a rise in the expression of genes linked to cell surface receptors. We conclude that a comparison of microglia transcriptomic activity during brain development and post-stroke adult brain might provide us with new clues about how neurodegeneration occurs in the adult brain. This information could very useful to develop drugs to slow down or limit the post-stroke pathology and improve clinical outcome.

Identification of the shared mechanisms and common biomarkers between Sjögren's syndrome and atherosclerosis using integrated bioinformatics analysis

Background

Sjögren's syndrome (SS) is a chronic autoimmune disease characterized by exocrine and extra-glandular symptoms. The literature indicates that SS is an independent risk factor for atherosclerosis (AS); however, its pathophysiological mechanism remains undetermined. This investigation aimed to elucidate the crosstalk genes and pathways influencing the pathophysiology of SS and AS via bioinformatic analysis of microarray data.

Methods

Microarray datasets of SS (GSE40611) and AS (GSE28829) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were acquired using R software's "limma" packages, and the functions of common DEGs were determined using Gene Ontology and Kyoto Encyclopedia analyses. The protein-protein interaction (PPI) was established using the STRING database. The hub genes were assessed via cytoHubba plug-in and validated by external validation datasets (GSE84844 for SS; GSE43292 for AS). Gene set enrichment analysis (GSEA) and immune infiltration of hub genes were also conducted.

Results

Eight 8 hub genes were identified using the intersection of four topological algorithms in the PPI network. Four genes (CTSS, IRF8, CYBB, and PTPRC) were then verified as important cross-talk genes between AS and SS with an area under the curve (AUC) ≥0.7. Furthermore, the immune infiltration analysis revealed that lymphocytes and macrophages are essentially linked with the pathogenesis of AS and SS. Moreover, the shared genes were enriched in multiple metabolisms and autoimmune disease-related pathways, as evidenced by GSEA analyses.

Conclusion

This is the first study to explore the common mechanism between SS and AS. Four key genes, including CTSS, CYBB, IRF8, and PTPRC, were associated with the pathogenesis of SS and AS. These hub genes and their correlation with immune cells could be a potential diagnostic and therapeutic target.

The presence of intratumoral Porphyromonas gingivalis correlates with a previously defined pancreatic adenocarcinoma, immune cell expression phenotype and with tumor resident, adaptive immune receptor features

The association between pancreatic adenocarcinoma (PAAD) and the pancreatic microbiome is not fully understood, although bacteria may decrease the effectiveness of chemotherapy and lead to anti-apoptotic, pro-inflammatory microenvironments. To better understand the relationship between the PAAD microbiome and the microenvironment, we identified Porphyromonas gingivalis-positive PAAD samples and found a strong association between intratumoral P. gingivalis and: (i) an immune cell gene expression phenotype previously defined by others as gene program 7; and (ii) recovery of immunoglobulin recombination, sequencing reads. We applied a novel chemical complementarity scoring algorithm, suitable for a big data setting, and determined that the previously established P. gingivalis antigen, rpgB had a reduced chemical complementarity with T-cell receptor (TCR) complementarity-determining region-3 amino acid sequences recovered from PAAD samples with P. gingivalis in comparison to TCR-rpgB chemical complementarity represented by the PAAD samples that lacked P. gingivalis. This finding strengthens the existing body of evidence correlating P. gingivalis with PAAD, which may have implications for the treatment and prognosis of patients. Furthermore, demonstrating the correlation of P. gingivalis and gene program 7 raises the question of whether P. gingivalis infection is responsible for the gene program 7 subdivision of PAAD?

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.

Neuroglia Cells Transcriptomic in Brain Development, Aging and Neurodegenerative Diseases

Glia cells are essential for brain functioning during development, aging and disease. However, the role of astroglia plays during brain development is quite different from the role played in the adult lesioned brain. Therefore, a deeper understanding of pathomechanisms underlying astroglia activity in the aging brain and cerebrovascular diseases is essential to guide the development of new therapeutic strategies. To this end, this review provides a comparison between the transcriptomic activity of astroglia cells during development, aging and neurodegenerative diseases, including cerebral ischemia. During fetal brain development, astrocytes and microglia often affect the same developmental processes such as neuro-/gliogenesis, angiogenesis, axonal outgrowth, synaptogenesis, and synaptic pruning. In the adult brain astrocytes are a critical player in the synapse remodeling by mediating synapse elimination while microglia activity has been associated with changes in synaptic plasticity and remove cell debris by constantly sensing the environment. However, in the lesioned brain astrocytes proliferate and play essential functions with regard to energy supply to the neurons, neurotransmission and buildup of a protective scar isolating the lesion site from the surroundings. Inflammation, neurodegeneration, or loss of brain homeostasis induce changes in microglia gene expression, morphology, and function, generally referred to as "primed" microglia. These changes in gene expression are characterized by an enrichment of phagosome, lysosome, and antigen presentation signaling pathways and is associated with an up-regulation of genes encoding cell surface receptors. In addition, primed microglia are characterized by upregulation of a network of genes in response to interferon gamma. Conclusion. A comparison of astroglia cells transcriptomic activity during brain development, aging and neurodegenerative disorders might provide us with new therapeutic strategies with which to protect the aging brain and improve clinical outcome.

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.

The commonness in immune infiltration of rheumatoid arthritis and atherosclerosis: Screening for central targets via microarray data analysis

Background

Although increasing evidence has reported an increased risk of atherosclerosis (AS) in rheumatoid arthritis (RA), the communal molecular mechanism of this phenomenon is still far from being fully elucidated. Hence, this article aimed to explore the pathogenesis of RA complicated with AS.

Methods

Based on the strict inclusion/exclusion criteria, four gene datasets were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the communal differentially expressed genes (DEGs) and hub genes, comprehensive bioinformatics analysis, including functional annotation, co-expression analysis, expression validation, drug-gene prediction, and TF-mRNA-miRNA regulatory network construction, was conducted. Moreover, the immune infiltration of RA and AS was analyzed and compared based on the CIBERSORT algorithm, and the correlation between hub genes and infiltrating immune cells was evaluated in RA and AS respectively.

Results

A total of 54 upregulated and 12 downregulated communal DEGs were screened between GSE100927 and GSE55457, and functional analysis of these genes indicated that the potential pathogenesis lies in immune terms. After the protein-protein interaction (PPI) network construction, a total of six hub genes (CCR5, CCR7, IL7R, PTPRC, CD2, and CD3D) were determined as hub genes, and the subsequent comprehensive bioinformatics analysis of the hub genes re-emphasized the importance of the immune system in RA and AS. Additionally, three overlapping infiltrating immune cells were found between RA and AS based on the CIBERSORT algorithm, including upregulated memory B cells, follicular helper T cells and γδT cells.

Conclusions

Our study uncover the communal central genes and commonness in immune infiltration between RA and AS, and the analysis of six hub genes and three immune cells profile might provide new insights into potential pathogenesis therapeutic direction of RA complicated with AS.

Clinical assessment and molecular mechanism of the upregulation of Toll-like receptor 2 (TLR2) in myocardial infarction

Objective

The prevalence and mortality of cardiovascular diseases remain ranked first worldwide. Myocardial infarction (MI) is the central cause of death from cardiovascular diseases, seriously endangering human health. The clinical implication of toll-like receptor 2 (TLR2) remains contradictory, and its mechanism is still unknown. Hence, the objective of this study was to elucidate the clinical value and molecular mechanism of TLR2 in MI.

Methods

All high-throughput datasets and eligible literature were screened, and the expression levels of TLR2 were collected from the MI. The integrated expression level of TLR2 was displayed by calculating the standardized mean difference (SMD) and the area under the curve (AUC) of the summary receiver operating characteristic curve (sROC). The related TLR2 genes were sent for pathway analyses by gene ontology (GO), Kyoto encyclopedia of genes and genome (KEGG), and disease ontology (DO). Single-cell RNA-seq was applied to ascertain the molecular mechanism of TLR2 in MI.

Results

Nine microarrays and four reported data were available to calculate the comprehensive expression level of TLR2 in MI, including 325 cases of MI and 306 cases of controls. The SMD was 2.55 (95% CI = 1.35–3.75), and the AUC was 0.76 (95% CI = 0.72–0.79), indicating the upregulation of TLR2 in MI. The related TLR2 genes were primarily enriched in the pathways of atherosclerosis, arteriosclerotic cardiovascular disease, and arteriosclerosis, suggesting the clinical role of TLR2 in the progression of MI. Afterward, TLR2 was upregulated in myeloid cells in MI.

Conclusions

TLR2 may have a crucial role in progressing from coronary atherosclerosis to MI. The upregulation of TLR2 may have a favorable screening value for MI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02754-y.

Heterogeneous Population of Immune cells Associated with Early Thrombosis in Arteriovenous Fistula

End-Stage Renal Disease (ESRD) is a growing cause of morbidity and mortality in the practice of modern medicine. Advances in medicine have elongated the average life span and subsequently made chronic diseases prevalent. Hemodialysis is the main treatment that is used to treat ESRD and is a clinical procedure that is being re-imagined with novel approaches to improve patient and clinic practicality and effectiveness. Arteriovenous Fistulas (AVF) are now used in place of catheters due to their higher success and lower co-morbidities. The main drawback of AVF is the time gap that is needed from the surgical creation of AVF to its use. During this time, the AVF is susceptible to thrombosis and occlusion rendering the fistula ineffective for treatment. Immune cells play a major role in vascular pathologies and macrophages, dendritic cells, and T-regulatory cells are the main cells seen during the inflammatory and anti-inflammatory phases. However, the role of immune response and immune cells in AVF maturation is poorly understood. This study aimed to investigate the immune response and immune cell expression in femoral vessels after AVF creation in a miniswine model of AVF using immunohistochemistry and qRT-PCR. The results of this study revealed an increased expression of immune cells in AVF vessels and suggest an association of immune response with AVF creation and maturation.

Pyroptosis-Related Gene Signature and Expression Patterns in the Deterioration of Atherosclerosis

Background

Pyroptosis has been shown to be involved in the overall process of atherosclerosis. This study was aimed at investigating pyroptosis-related gene expression patterns in atherosclerosis and their diagnostic significance.

Methods and Results

In GSE100927, fifty-four pyroptosis-related genes were identified. Between atherosclerotic plaques and normal samples, the expression patterns of pyroptosis-related genes were significantly different. In order to construct a pyroptosis-related risk score signature (PRSS), the least absolute shrinkage and selection operator (LASSO) was combined with multivariate logistic regression to screen twelve genes. The diagnostic efficiency of the PRSS performed well in GSE43292, as shown by the results of receiver-operating characteristics (ROCs). Consensus clustering identified two expression patterns of pyroptosis-related genes in different statuses of atherosclerotic plaque in GSE163154. The biological behavior of the different clusters was examined by the gene set variation analysis (GSVA). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses revealed that the differentially expressed genes (DEGs) in the two clusters were enriched in the immune response. The Cytoscape software was used to construct protein-protein interaction (PPI) networks for hub gene screening. Following that, the Drug Gene Interaction Database (DGIdb) was utilized to find 47 possible medicines and chemical compounds that interact with hub genes in atherosclerotic plaques.

Conclusion

The results of this study showed that pyroptosis-related genes contribute to the progression of atherosclerosis and may serve as biomarkers in clinical diagnosis as well as novel therapeutic targets for the treatment of AS.

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.

Inflammation and atherosclerosis: signaling pathways and therapeutic intervention

Atherosclerosis is a chronic inflammatory vascular disease driven by traditional and nontraditional risk factors. Genome-wide association combined with clonal lineage tracing and clinical trials have demonstrated that innate and adaptive immune responses can promote or quell atherosclerosis. Several signaling pathways, that are associated with the inflammatory response, have been implicated within atherosclerosis such as NLRP3 inflammasome, toll-like receptors, proprotein convertase subtilisin/kexin type 9, Notch and Wnt signaling pathways, which are of importance for atherosclerosis development and regression. Targeting inflammatory pathways, especially the NLRP3 inflammasome pathway and its regulated inflammatory cytokine interleukin-1β, could represent an attractive new route for the treatment of atherosclerotic diseases. Herein, we summarize the knowledge on cellular participants and key inflammatory signaling pathways in atherosclerosis, and discuss the preclinical studies targeting these key pathways for atherosclerosis, the clinical trials that are going to target some of these processes, and the effects of quelling inflammation and atherosclerosis in the clinic.

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.

Monocyte-related gene biomarkers for latent and active tuberculosis

Monocytes are closely associated with tuberculosis (TB). Latent tuberculosis in some patients gradually develops into its active state. This study aimed to investigate the role of hub monocyte-associated genes in distinguishing latent TB infection (LTBI) from active TB. The gene expression profiles of 15 peripheral blood mononuclear cells (PBMCs) samples were downloaded from the gene expression omnibus (GEO) database, GSE54992. The monocyte abundance was high in active TB as evaluated by the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm. The limma test and correlation analysis documented 165 differentially expressed monocyte-related genes (DEMonRGs) between latent TB and active TB. Functional annotation and enrichment analyses of the DEMonRGs using the database for annotation, visualization, and integration discovery (DAVID) tools showed enrichment of inflammatory response mechanisms and immune-related pathways. A protein-protein interaction network was constructed with a node degree ≥10. The expression levels of these hub DEMonRGs (SERPINA1, FUCA2, and HP) were evaluated and verified using several independent datasets and clinical settings. Finally, a single sample scoring method was used to establish a gene signature for the three DEMonRGs, distinguishing active TB from latent TB. The findings of the present study provide a better understanding of monocyte-related molecular fundamentals in TB progression and contribute to the identification of new potential biomarkers for the diagnosis of active TB.