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

Mechanism of Xue-Jie-San treating Crohn's disease complicated by atherosclerosis: Network pharmacology, molecular docking and experimental validation

BACKGROUND

Crohn's disease (CD), as a chronic systemic inflammatory disease, is strongly associated with the development of premature atherosclerosis (AS). Atherosclerotic cardiovascular disease, including coronary heart disease, myocardial infarction and stroke, is a lethal complication of CD. Nowadays, there is a lack of effective monotherapy for CD complicated by AS.

PURPOSE

To explore the underlying effects and mechanisms of Xue-Jie-San (XJS) on treating CD complicated by AS via network pharmacology and experimental validation.

METHODS

The targets of XJS components were obtained from TCMSP, ETCM and PubChem databases as well as the disease genes of CD and AS from GeneCards, DisGeNET and OMIM databases. The core targets were screened out from the drug-disease common targets identified by protein-protein interaction (PPI) network analysis and then analyzed with GO and KEGG enrichment. The interaction between core target and XJS component was detected by molecular docking and molecular dynamics simulation. Subsequently, the core targets were validated via GEO datasets and their biological functions were confirmed in vitro. Nile red staining was used to evaluated lipid accumulation in human umbilical vein endothelial cells (HUVECs) challenged by lipopolysaccharide (LPS) combined with oxidized low-density lipoprotein (ox-LDL). Levels of pro-inflammatory cytokines were examined by enzyme-linked immunosorbent assay. Chemokine CCL2 and CXCL8 were detected by immunofluorescence staining. The activity of the TLR4/Myd88/NF-κB signaling pathway was assessed using Western blot.

RESULTS

In total, 26 common target genes of XJS, CD and AS were found. Among them, 11 core genes were identified by PPI network analysis. The effects of XJS treating CD complicated by AS were mainly mediated by the lipid and atherosclerosis pathway, inflammatory bowel disease pathway and toll-like receptor signaling pathway. Molecular docking and molecular dynamics simulation displayed strong binding affinity between XJS component and the core target. Six core genes including TLR4, IL-1β, TNF, ICAM1, CCL2 and CXCL8 were validated by GEO datasets. In vitro, the effects of XJS on reducing lipid accumulation, secretion of IL-1β, IL6, TNF-α, CCL2 and CXCL8, and the protein expressions of TLR4, Myd88, p-p65 and ICAM1 were verified.

CONCLUSION

XJS is a potential candidate drug for the treatment of CD complicated by AS. The underlying mechanisms involve mitigation of lipid accumulation-mediated endothelial dysfunction and blockage of immune inflammatory response by targeting TLR4.

Identification of common mechanisms and biomarkers for dermatomyositis and atherosclerosis based on bioinformatics analysis

BACKGROUND

Dermatomyositis (DM) manifests as an autoimmune and inflammatory condition, clinically characterized by subacute progressive proximal muscle weakness, rashes or both along with extramuscular manifestations. Literature indicates that DM shares common risk factors with atherosclerosis (AS), and they often co-occur, yet the etiology and pathogenesis remain to be fully elucidated. This investigation aims to utilize bioinformatics methods to clarify the crucial genes and pathways that influence the pathophysiology of both DM and AS.

METHOD

Microarray datasets for DM (GSE128470, GSE1551, GSE143323) and AS (GSE100927, GSE28829, GSE43292) were retrieved from the Gene Expression Omnibus (GEO) database. The weighted gene co-expression network analysis (WGCNA) was used to reveal their co-expressed modules. Differentially expression genes (DEGs) were identified using the "limma" package in R software, and the functions of common DEGs were determined by functional enrichment analysis. A protein-protein interaction (PPI) network was established using the STRING database, with central genes evaluated by the cytoHubba plugin, and validated through external datasets. Immune infiltration analysis of the hub genes was conducted using the CIBERSORT method, along with Gene Set Enrichment Analysis (GSEA). Finally, the NetworkAnalyst platform was employed to examine the transcription factors (TFs) responsible for regulating pivotal crosstalk genes.

RESULTS

Utilizing WGCNA analysis, a total of 271 overlapping genes were pinpointed. Subsequent DEG analysis revealed 34 genes that are commonly found in both DM and AS, including 31 upregulated genes and 3 downregulated genes. The Degree Centrality algorithm was applied separately to the WGCNA and DEG collections to select the 15 genes with the highest connectivity, and crossing the two gene sets yielded 3 hub genes (PTPRC, TYROBP, CXCR4). Validation with external datasets showed their diagnostic value for DM and AS. Analysis of immune infiltration indicates that lymphocytes and macrophages are significantly associated with the pathogenesis of DM and AS. Moreover, GSEA analysis suggested that the shared genes are enriched in various receptor interactions and multiple cytokines and receptor signaling pathways. We coupled the 3 hub genes with their respective predicted genes, identifying a potential key TF, CBFB, which interacts with all 3 hub genes.

CONCLUSION

This research utilized comprehensive bioinformatics techniques to explore the shared pathogenesis of DM and AS. The three key genes, including PTPRC, TYROBP, and CXCR4, are related to the pathogenesis of DM and AS. The central genes and their correlations with immune cells may serve as potential diagnostic and therapeutic targets.

Identification of idiopathic pulmonary fibrosis hub genes and exploration of the mechanisms of action of Jinshui Huanxian formula

Idiopathic pulmonary fibrosis (IPF) is a common and heterogeneous chronic disease, and the mechanism of Jinshui Huanxian formula (JHF) on IPF remains unclear. For a total of 385 lung normal tissue samples from the Gene Expression Omnibus database, 37,777,639 gene pairs were identified through microarray and RNA-seq platforms. Using the individualized differentially expressed gene (DEG) analysis algorithm RankComp (FDR < 0.01), we identified 344 genes as DEGs in at least 95 % (n = 81) of the IPF samples. Of these genes, IGF1, IFNGR1, GLI2, HMGCR, DNM1, KIF4A, and TNFRSF11A were identified as hub genes. These genes were verified using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in mice with pulmonary fibrosis (PF) and MRC-5 cells, and they were highly effective at classifying IPF samples in the independent dataset GSE134692 (AUC = 0.587-0.788) and mice with PF (AUC = 0.806-1.000). Moreover, JHF ameliorated the pathological changes in mice with PF and significantly reversed the changes in hub gene expression (KIF4A, IFNGR1, and HMGCR). In conclusion, a series of IPF hub genes was identified, and validated in an independent dataset, mice with PF, and MRC-5 cells. Moreover, the abnormal gene expression was normalized by JHF. These findings provide guidance for further exploration of the pathogenesis and treatment of IPF.

Emerging role of exosomes in ulcerative colitis: Targeting NOD-like receptor family pyrin domain containing 3 inflammasome

Ulcerative colitis (UC) is a chronic recurrent inflammatory bowel disease. Despite ongoing advances in our understanding of UC, its pathogenesis is yet unelucidated, underscoring the urgent need for novel treatment strategies for patients with UC. Exosomes are nanoscale membrane particles that mediate intercellular communication by carrying various bioactive molecules, such as proteins, RNAs, DNA, and metabolites. The NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome is a cytosolic tripartite protein complex whose activation induces the maturation and secretion of proinflammatory cytokines interleukin-1β (IL-1β) and IL-18, triggering the inflammatory response to a pathogenic agent or injury. Growing evidence suggests that exosomes are new modulators of the NLRP3 inflammasome, with vital roles in the pathological process of UC. Here, recent evidence is reviewed on the role of exosomes and NLRP3 inflammasome in UC. First, the dual role of exosomes on NLRP3 inflammasome and the effect of NLRP3 inflammasome on exosome secretion are summarized. Finally, an outlook on the directions of exosome-NLRP3 inflammasome crosstalk research in the context of UC is proposed and areas of further research on this topic are highlighted.

Research hotspots and trends of artificial intelligence in rheumatoid arthritis: A bibliometric and visualized study

Artificial intelligence (AI) applications on rheumatoid arthritis (RA) are becoming increasingly popular. In this bibliometric study, we aimed to analyze the characteristics of publications relevant to the research of AI in RA, thereby developing a thorough overview of this research topic. Web of Science was used to retrieve publications on the application of AI in RA from 2003 to 2022. Bibliometric analysis and visualization were performed using Microsoft Excel (2019), R software (4.2.2) and VOSviewer (1.6.18). The overall distribution of yearly outputs, leading countries, top institutions and authors, active journals, co-cited references and keywords were analyzed. A total of 859 relevant articles were identified in the Web of Science with an increasing trend. USA and China were the leading countries in this field, accounting for 71.59% of publications in total. Harvard University was the most influential institution. Arthritis Research & Therapy was the most active journal. Primary topics in this field focused on estimating the risk of developing RA, diagnosing RA using sensor, clinical, imaging and omics data, identifying the phenotype of RA patients using electronic health records, predicting treatment response, tracking the progression of the disease and predicting prognosis and developing new drugs. Machine learning and deep learning algorithms were the recent research hotspots and trends in this field. AI has potential applications in various fields of RA, including the risk assessment, screening, early diagnosis, monitoring, prognosis determination, achieving optimal therapeutic outcomes and new drug development for RA patients. Incorporating machine learning and deep learning algorithms into real-world clinical practice will be a future research hotspot and trend for AI in RA. Extensive collaboration to improve model maturity and robustness will be a critical step in the advancement of AI in healthcare.

Macrophages in ulcerative colitis: A perspective from bibliometric and visual analysis

Objectives

Despite the many reported studies on macrophages in ulcerative colitis (UC), the overall research trends in this field are unclear. This study evaluates the research trends and hotspots regarding macrophages in UC using bibliometric analysis.

Methods

A systematic search was conducted in the Web of Science database to identify publications related to macrophages in UC from 2012 to 2021. R package 'bibliometrix', VOSviewers, CiteSpace and Microsoft Excel were utilised for the bibliometric analysis.

Results

1074 articles published between 2012 and 2021 were analysed. The number of publications on macrophages in UC showed a consistently increasing trend, with USA and China as the leading contributors to this field. Notably, Georgia State University and Nanjing University contributed significantly to this field. Among the authors, Wang Y had the highest productivity, while Wu X received the most citations. The journal Gut was identified as the most authoritative journal in this field. Co-citation analysis revealed that the exploration of the mechanisms of macrophages in UC through in vivo and in vitro experiments was the primary focus of research. Moreover, the emerging research hotspots included keywords such as 'macrophage polarization', 'gut microbiota' and 'NLRP3 inflammasome'.

Conclusions

Research on macrophages in UC holds significant value and practical implications. Additionally, China demonstrated prolific output in this field, while the USA had the most influential contributions. Currently, research hotspots are centred around the modulation of gut microbiota to regulate macrophage polarization and macrophage pyroptosis as potential strategies for mitigating UC.