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Identification of neutrophil extracellular traps and crosstalk genes linking inflammatory bowel disease and osteoporosis by integrated bioinformatics analysis and machine learning.

ABSTRACT: Musculoskeletal deficits are among the most common extra-intestinal manifestations and complications of inflammatory bowel disease (IBD). This study aimed to identify crosstalk genes between IBD and osteoporosis (OP) and potential relationships between crosstalk and neutrophil extracellular traps (NETs)-related genes. Three common hub genes from different compared groups are actually the same, namely HDAC6, IL-8, and PPIF. ROC showed that the combined diagnostic value of HDAC6, IL-8, and PPIF was higher than each of the three key hub genes. Immune infiltration results showed that HDAC6 and IL-8 key genes negatively correlated with CD65 bright natural killer cells. USF1 was the common upstream TFs between HDAC6 and PPIF, and MYC was the common upstream TFs between IL-8 and PPIF in RegNetwork. Taken together, this study shows a linked mechanism between IBD and OP via NETs and crosstalk genes. These findings may show light on better diagnosis and treatment of IBD complicated with OP.

SUBMITTER: Xu G

PROVIDER: S-EPMC10754907 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Identification of neutrophil extracellular traps and crosstalk genes linking inflammatory bowel disease and osteoporosis by integrated bioinformatics analysis and machine learning.

Xu Gang G Zhang Wanhao W Yang Jun J Sun Na N Qu Xiaochen X

Scientific reports 20231227 1

Musculoskeletal deficits are among the most common extra-intestinal manifestations and complications of inflammatory bowel disease (IBD). This study aimed to identify crosstalk genes between IBD and osteoporosis (OP) and potential relationships between crosstalk and neutrophil extracellular traps (NETs)-related genes. Three common hub genes from different compared groups are actually the same, namely HDAC6, IL-8, and PPIF. ROC showed that the combined diagnostic value of HDAC6, IL-8, and PPIF wa ...[more]

PMID: 38155235

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Project description:Background and objectiveThis study aimed to identify crosstalk genes between periodontitis (PD) and osteoporosis (OP) and potential relationships between crosstalk and pyroptosis-related genes.MethodsPD and OP datasets were downloaded from the GEO database and were performed differential expression analysis to obtain DEGs. Overlapping DEGs got crosstalk genes linking PD and OP. Pyroptosis-related genes were obtained from literature reviews. Pearson coefficients were used to calculate crosstalk and pyroptosis-related gene correlations in the PD and OP datasets. Paired genes were obtained from the intersection of correlated genes in PD and OP. PINA and STRING databases were used to conduct the crosstalk-bridge-pyroptosis genes PPI network. The clusters in which crosstalk and pyroptosis-related genes were mainly concentrated were defined as key clusters. The key clusters' hub genes and the included paired genes were identified as key crosstalk-pyroptosis genes. Using ROC curve analysis and XGBoost screened key genes. PPI subnetwork, gene-biological process and gene-pathway networks were constructed based on key genes. In addition, immune infiltration was analyzed on the PD dataset using the CIBERSORT algorithm.ResultsA total of 69 crosstalk genes were obtained. 13 paired genes and hub genes TNF and EGFR in the key clusters (cluster2, cluster8) were identified as key crosstalk-pyroptosis genes. ROC and XGBoost showed that PRKCB, GSDMD, ARMCX3, and CASP3 were more accurate in predicting disease than other key crosstalk-pyroptosis genes while better classifying properties as a whole. KEGG analysis showed that PRKCB, GSDMD, ARMCX3, and CASP3 were involved in neutrophil extracellular trap formation and MAPK signaling pathway pathways. Immune infiltration results showed that all four key genes positively correlated with plasma cells and negatively correlated with T cells follicular helper, macrophages M2, and DCs.ConclusionThis study shows a joint mechanism between PD and OP through crosstalk and pyroptosis-related genes. The key genes PRKCB, GSDMD, ARMCX3, and CASP3 are involved in the neutrophil extracellular trap formation and MAPK signaling pathway, affecting both diseases. These findings may point the way to future research.

Project description:The development of unstable carotid atherosclerotic plaques is associated with the induction of neutrophil extracellular traps (NETs) via the activation of diverse inflammatory mediators in the circulating bloodstream. However, the underlying mechanisms through which NETs influence the microenvironment of atherosclerotic plaques and contribute to the development of unstable carotid plaques remain largely elusive. The objective of this study was to elucidate the role of myeloid differentiation protein 1 (MD-1, LY86)-induced NETs underlying the crosstalk between unstable plaque formation and the plaque microenvironment. We employed bioinformatics analysis to identify key genes associated with carotid-unstable plaque, followed by comprehensive validation using various experimental approaches on tissue specimens and plasma samples classified based on pathological characteristics. Patients with carotid-unstable plaques exhibited elevated plasma concentrations of MD-1 (LY86), while patients with stable plaques demonstrated comparatively lower levels. Furthermore, soluble MD-1 was found to induce the formation of NETs through activation of Toll-like receptor signaling pathway. The proliferative and immature vascularization effects of NETs on endothelial cells, as well as their inhibitory impact on cell migration, are directly correlated with the concentration of NETs. Additionally, NETs were found to activate the NF-κB signaling pathway, thereby upregulating ICAM1, VCAM1, MMP14, VEGFA, and IL6 expression in both Human umbilical vein endothelial cells (HUVECs) and HAECs. Subsequently, a significant increase in intraplaque neovascularization by NETs results in poor carotid plaque stability, and NETs in turn stimulate macrophages to produce more MD-1, generating a harmful positive feedback loop. Our findings suggest that soluble MD-1 in the bloodstream triggers the production of NETs through activation of the Toll-like receptor signaling pathway and further indicate NETs mediate a crosstalk between the microenvironment of the carotid plaque and the neovascularization of the intraplaque region. Inhibiting NETs formation or MD-1 secretion may represent a promising strategy to effectively suppress the development of unstable carotid plaques.

Project description:BackgroundRheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial inflammation and progressive joint destruction. Neutrophil extracellular traps (NETs), a microreticular structure formed after neutrophil death, have recently been implicated in RA pathogenesis and pathological mechanisms. However, the underlying molecular mechanisms and key genes involved in NET formation in RA remain largely unknown.MethodsWe obtained single-cell RNA sequencing data of synovial tissues from the Gene Expression Omnibus (GEO) database and performed cellular annotation and intercellular communication analyses. Subsequently, three microarray datasets were collected for a training cohort and correlated with a bulk RNA-seq dataset associated with NETs. Differentially expressed genes were identified, and weighted gene correlation network analysis was used to characterize gene association. Using three machine learning techniques, we identified the most important hub genes to develop and evaluate a nomogram diagnostic model. CIBERSORT was used to elucidate the relationship between hub genes and immune cells. An external validation dataset was used to verify pivotal gene expression and to construct co-regulatory networks using the NetworkAnalyst platform. We further investigated hub gene expression using immunohistochemistry (IHC) in an adjuvant-induced arthritis rat model and real-time quantitative polymerase chain reaction (RT-qPCR) in a clinical cohort.ResultsSeven cellular subpopulations were identified through downscaling and clustering, with neutrophils likely the most crucial cell clusters in RA. Intercellular communication analysis highlighted the network between neutrophils and fibroblasts. In this context, 4 key hub genes (CRYBG1, RMM2, MMP1, and SLC19A2) associated with NETs were identified. A nomogram model with a diagnostic value was developed and evaluated. Immune cell infiltration analysis indicated associations between the hub genes and the immune landscape in NETs and RA. IHC and RT-qPCR findings showed high expression of CRYBG1, RMM2, and MMP1 in synovial and neutrophilic cells, with lower expression of SLC19A2. Correlation analysis further emphasized close associations between hub genes and laboratory markers in patients with RA.ConclusionThis study first elucidated neutrophil heterogeneity in the RA synovial microenvironment and mechanisms of communication with fibroblasts. CRYBG1, RMM2, MMP1, and SLC19A2 were identified and validated as potential NET-associated biomarkers, offering insights for diagnostic tools and immunotherapeutic strategies in RA.

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Identification of neutrophil extracellular traps and crosstalk genes linking inflammatory bowel disease and osteoporosis by integrated bioinformatics analysis and machine learning.

Publications

Identification of neutrophil extracellular traps and crosstalk genes linking inflammatory bowel disease and osteoporosis by integrated bioinformatics analysis and machine learning.

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