Neutrophil Infiltration Characterized by Upregulation of S100A8, S100A9, S100A12 and CXCR2 Is Associated With the Co-Occurrence of Crohn’s Disease and Peripheral Artery Disease

Endothelial CXCR2 deficiency attenuates renal inflammation and glycocalyx shedding through NF-κB signaling in diabetic kidney disease

BACKGROUND

The incidence of diabetic kidney disease (DKD) continues to rapidly increase, with limited available treatment options. One of the hallmarks of DKD is persistent inflammation, but the underlying molecular mechanisms of early diabetic kidney injury remain poorly understood. C-X-C chemokine receptor 2 (CXCR2), plays an important role in the progression of inflammation-related vascular diseases and may bridge between glomerular endothelium and persistent inflammation in DKD.

METHODS

Multiple methods were employed to assess the expression levels of CXCR2 and its ligands, as well as renal inflammatory response and endothelial glycocalyx shedding in patients with DKD. The effects of CXCR2 on glycocalyx shedding, and persistent renal inflammation was examined in a type 2 diabetic mouse model with Cxcr2 knockout specifically in endothelial cells (DKD-Cxcr2 eCKO mice), as well as in glomerular endothelial cells (GECs), cultured in high glucose conditions.

RESULTS

CXCR2 was associated with early renal decline in DKD patients, and endothelial-specific knockout of CXCR2 significantly improved renal function in DKD mice, reduced inflammatory cell infiltration, and simultaneously decreased the expression of proinflammatory factors and chemokines in renal tissue. In DKD conditions, glycocalyx shedding was suppressed in endothelial Cxcr2 knockout mice compared to Cxcr2 L/L mice. Modulating CXCR2 expression also affected high glucose-induced inflammation and glycocalyx shedding in GECs. Mechanistically, CXCR2 deficiency inhibited the activation of NF-κB signaling, thereby regulating inflammation, restoring the endothelial glycocalyx, and alleviating DKD.

CONCLUSIONS

Taken together, under DKD conditions, activation of CXCR2 exacerbates inflammation through regulation of the NF-κB pathway, leading to endothelial glycocalyx shedding and deteriorating renal function. Endothelial CXCR2 deficiency has a protective role in inflammation and glycocalyx dysfunction, suggesting its potential as a promising therapeutic target for DKD treatment.

Identification and validation of hub genes expressed in ulcerative colitis with metabolic dysfunction-associated steatotic liver disease

Objective

Ulcerative colitis (UC) and metabolic dysfunction-associated steatotic liver disease (MASLD) are closely intertwined; however, the precise molecular mechanisms governing their coexistence remain unclear.

Methods

We obtained UC (GSE75214) and MASLD (GSE151158) datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were acquired by the 'edgeR' and 'limma' packages of R. We then performed functional enrichment analysis of common DEGs. Hub genes were selected using the cytoHubba plugin and validated using GSE87466 for UC and GSE33814 for MASLD. Immunohistochemistry was employed to validate the hub genes' expression in clinical samples. Immune infiltration and gene set enrichment analyses of the hub genes were performed. Finally, we estimated the Spearman's correlation coefficients for the clinical correlation of the core genes.

Results

Within a cohort of 26 differentially regulated genes in both UC and MASLD, pathways involving cytokine-mediated signaling, cell chemotaxis, and leukocyte migration were enriched. After further validation, CXCR4, THY1, CCL20, and CD2 were identified as the hub genes. Analysis of immune infiltration patterns highlighted an association between elevated pivotal gene expression and M1 macrophage activation. Immunohistochemical staining revealed widespread expression of pivotal genes in UC- and MASLD-affected tissues. Furthermore, significant correlations were observed between the increased expression of hub genes and biochemical markers, such as albumin and prothrombin time.

Conclusion

This bioinformatics analysis highlights CXCR4, THY1, CCL20, and CD2 as crucial genes involved in the co-occurrence of UC and MASLD, providing insights into the underlying mechanisms of these two conditions.

CD8+ T and NK cells characterized by upregulation of NPEPPS and ABHD17A are associated with the co-occurrence of type 2 diabetes and coronary artery disease

Background

Coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) are closely related. The function of immunocytes in the pathogenesis of CAD and T2DM has not been extensively studied. The quantitative bioinformatics analysis of the public RNA sequencing database was applied to study the key genes that mediate both CAD and T2DM. The biological characteristics of associated key genes and mechanism of CD8+ T and NK cells in CAD and T2DM are our research focus.

Methods

With expression profiles of GSE66360 and GSE78721 from the Gene Expression Omnibus (GEO) database, we identified core modules associated with gene co-expression relationships and up-regulated genes in CAD and T2DM using Weighted Gene Co-expression Network Analysis (WGCNA) and the 'limma' software package. The enriched pathways of the candidate hub genes were then explored using GO, KEGG and GSEA in conjunction with the immune gene set (from the MSigDB database). A diagnostic model was constructed using logistic regression analysis composed of candidate hub genes in CAD and T2DM. Univariate Cox regression analysis revealed hazard ratios (HRs), 95% confidence intervals (CIs), and p-values for candidate hub genes in diagnostic model, while CIBERSORT and immune infiltration were used to assess the immune microenvironment. Finally, monocytes from peripheral blood samples and their immune cell ratios were analyzed by flow cytometry to validate our findings.

Results

Sixteen candidate hub genes were identified as being correlated with immune infiltration. Univariate Cox regression analysis revealed that NPEPPS and ABHD17A were highly correlated with the diagnosis of CAD and T2DM. The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM. The bioinformatics results on immune infiltration were well validated by flow cytometry.

Conclusions

A series of bioinformatics studies have shown ABHD17A and NPEPPS as key genes for the co-occurrence of CAD and T2DM. Our study highlights the important effect of CD8+ T and NK cells in the pathogenesis of both diseases, indicating that they may serve as viable targets for diagnosis and therapeutic intervention.

Identification CCL2,CXCR2,S100A9 of the immune-related gene markers and immune infiltration characteristics of inflammatory bowel disease and heart failure via bioinformatics analysis and machine learning

Background

Recently, heart failure (HF) and inflammatory bowel disease (IBD) have been considered to be related diseases with increasing incidence rates; both diseases are related to immunity. This study aims to analyze and identify immune-related gene (IRG) markers of HF and IBD through bioinformatics and machine learning (ML) methods and to explore their immune infiltration characteristics.

Methods

This study used gene expressiondata (GSE120895, GSE21610, GSE4183) from the Gene Expression Omnibus (GEO) database to screen differentially expressed genes (DEGs) and compare them with IRGs from the ImmPort database to obtain differentially expressed immune-related genes (DIRGs). Functional enrichment analysis of IRGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, three machine models and protein-protein interactions (PPIs) were established to identify diagnostic biomarkers. The receiver operating characteristic (ROC) curves were applied to evaluate the diagnostic value of the candidate biomarkersin the validation set (GSE1145, GSE36807) and obtain their correlations with immune cells through the Spearman algorithm. Finally, the CIBERSORT algorithm was used to evaluate the immune cell infiltration of the two diseases.

Results

Thirty-four DIRGs were screened and GO and KEGG analysis results showed that these genes are mainly related to inflammatory and immune responses. CCL2, CXCR2 and S100A9 were identified as biomarkers.The immune correlation results indicated in both diseases that CCL2 is positively correlated with mast cell activation, CXCR2 is positively correlated with neutrophils and S100A9 is positively correlated with neutrophils and mast cell activation. Analysis of immune characteristics showed that macrophages M2, macrophages M0 and neutrophils were present in both diseases.

Conclusions

CCL2, CXCR2 and S100A9 are promising biomarkers that will become potential immunogenetic biomarkers for diagnosing comorbidities of HF and IBD. macrophages M2, macrophages M0, neutrophil-mediated inflammation and immune regulation play important roles in the development of HF and IBD and may become diagnostic and therapeutic targets.

Identification of hub biomarkers and immune-related pathways participating in the progression of Kawasaki disease by integrated bioinformatics analysis

BACKGROUND

Kawasaki disease (KD) is a systemic vasculitis that commonly affects children and its etiology remains unknown. Growing evidence suggests that immune-mediated inflammation and immune cells in the peripheral blood play crucial roles in the pathophysiology of KD. The objective of this research was to find important biomarkers and immune-related mechanisms implicated in KD, along with their correlation with immune cells in the peripheral blood.

MATERIAL/METHODS

Gene microarray data from the Gene Expression Omnibus (GEO) was utilized in this study. Three datasets, namely GSE63881 (341 samples), GSE73463 (233 samples), and GSE73461 (279 samples), were obtained. To find intersecting genes, we employed differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA). Subsequently, functional annotation, construction of protein-protein interaction (PPI) networks, and Least Absolute Shrinkage and Selection Operator (LASSO) regression were performed to identify hub genes. The accuracy of these hub genes in identifying KD was evaluated using the receiver operating characteristic curve (ROC). Furthermore, Gene Set Variation Analysis (GSVA) was employed to explore the composition of circulating immune cells within the assessed datasets and their relationship with the hub gene markers.

RESULTS

WGCNA yielded eight co-expression modules, with one hub module (MEblue module) exhibiting the strongest association with acute KD. 425 distinct genes were identified. Integrating WGCNA and DEGs yielded a total of 277 intersecting genes. By conducting LASSO analysis, five hub genes (S100A12, MMP9, TLR2, NLRC4 and ARG1) were identified as potential biomarkers for KD. The diagnostic value of these five hub genes was demonstrated through ROC curve analysis, indicating their high accuracy in diagnosing KD. Analysis of the circulating immune cell composition within the assessed datasets revealed a significant association between KD and various immune cell types, including activated dendritic cells, neutrophils, immature dendritic cells, macrophages, and activated CD8 T cells. Importantly, all five hub genes exhibited strong correlations with immune cells.

CONCLUSION

Activated dendritic cells, neutrophils, and macrophages were closely associated with the pathogenesis of KD. Furthermore, the hub genes (S100A12, MMP9, TLR2, NLRC4, and ARG1) are likely to participate in the pathogenic mechanisms of KD through immune-related signaling pathways.

Identification and Analysis of Necroptosis-Related Genes in COPD by Bioinformatics and Experimental Verification

Chronic obstructive pulmonary disease (COPD) is a heterogeneous and complex progressive inflammatory disease. Necroptosis is a newly identified type of programmed cell death. However, the role of necroptosis in COPD is unclear. This study aimed to identify necroptosis-related genes in COPD and explore the roles of necroptosis and immune infiltration through bioinformatics. The analysis identified 49 differentially expressed necroptosis-related genes that were primarily engaged in inflammatory immune response pathways. The infiltration of CD8+ T cells and M2 macrophages in COPD lung tissue was relatively reduced, whereas that of M0 macrophages was increased. We identified 10 necroptosis-related hub genes significantly associated with infiltrated immune cells. Furthermore, 7 hub genes, CASP8, IL1B, RIPK1, MLKL, XIAP, TNFRSF1A, and CFLAR, were validated using an external dataset and experimental mice. CFLAR was considered to have the best COPD-diagnosing capability. TF and miRNA interactions with common hub genes were identified. Several related potentially therapeutic molecules for COPD were also identified. The present findings suggest that necroptosis occurs in COPD pathogenesis and is correlated with immune cell infiltration, which indicates that necroptosis may participate in the development of COPD by interacting with the immune response.

Pathogenic roles of neutrophil-derived alarmins (S100A8/A9) in heart failure: From molecular mechanisms to therapeutic insights

An excessive neutrophil count is recognized as a valuable predictor of inflammation and is associated with a higher risk of adverse cardiac events in patients with heart failure. Our understanding of the effectors used by neutrophils to inflict proinflammatory actions needs to be advanced. Recently, emerging evidence has demonstrated a causative role of neutrophil-derived alarmins (i.e. S100A8/A9) in aggravating cardiac injuries by induction of inflammation. In parallel with the neutrophil count, high circulating levels of S100A8/A9 proteins powerfully predict mortality in patients with heart failure. As such, a deeper understanding of the biological functions of neutrophil-derived S100A8/A9 proteins would offer novel therapeutic insights. Here, the basic biology of S100A8/A9 proteins and their pleiotropic roles in cardiovascular diseases are discussed, focusing on heart failure. We also consider the evidence that therapeutic targeting of S100A8/A9 proteins by the humanized vaccine, antibodies or inhibitors is able to town down inflammatory injuries.

Identification of hub genes and biological mechanisms underlying the pathogenesis of asthenozoospermia and chronic epididymitis

Objective: Asthenozoospermia (AZS) is one of the most common causes of male fertility, affecting family wellbeing and population growth. Chronic epididymitis (CE) is a common and lingering inflammatory disease in the scrotum. Inflammation in the epididymis has a severe impact on sperm motility. This study aimed to explore the genetic profile and critical pathways involved in the pathological mechanisms of AZS and CE, and discover potential biomarkers. Methods: Genomic datasets of AZS and CE were obtained from the Gene Expression Omnibus (GEO) database, and relevant differentially expressed genes (DEGs) were identified. GO and pathway enrichment analyses, construction of a protein-protein interaction network, and receiver operator characteristic curve analysis were conducted. The expression profile of hub genes was validated in immunohistochemical data and testicular cell data. Immune infiltration, miRNA-hub gene interactions, and gene-disease interactions were explored. The mRNA levels of hub genes were further measured by qRT-PCR. Results: A total of 109 DEGs were identified between the AZS/CE and healthy control groups. Pathways of the immune system, neutrophil degranulation, and interleukin-4 and interleukin-13 signaling were enriched in AZS and CE. Five hub genes (CD300LB, CMKLR1, CCR4, B3GALT5, and CTSK) were selected, and their diagnostic values were validated in AZS, CE, and independent validation sets (area under the curve >0.7). Furthermore, the five-hub gene signature was well characterized in testicular immunohistochemical staining and testicular cells from healthy controls. Immune infiltration analysis showed that infiltration of CD8⁺ cells and T helper cells was significantly related to the expression level of five hub genes. In addition, a miRNA-hub gene network and interaction of other diseases were displayed. The mRNA levels of hub genes (CD300LB, CMKLR1, CCR4, and B3GALT5) were significantly elevated in the patient group. The mRNA level of CTSK also showed a similar trend. Conclusion: Our study uncovered the genetic profile involved in AZS and CE, and elucidated enriched pathways and molecular associations between hub genes and immune infiltration. This finding provides novel insight into the common pathogenesis of both diseases as well as the potential biomarkers for CE-associated AZS.

Identification of nine signature proteins involved in periodontitis by integrated analysis of TMT proteomics and transcriptomics

Recently, there are many researches on signature molecules of periodontitis derived from different periodontal tissues to determine the disease occurrence and development, and deepen the understanding of this complex disease. Among them, a variety of omics techniques have been utilized to analyze periodontitis pathology and progression. However, few accurate signature molecules are known and available. Herein, we aimed to screened and identified signature molecules suitable for distinguishing periodontitis patients using machine learning models by integrated analysis of TMT proteomics and transcriptomics with the purpose of finding novel prediction or diagnosis targets. Differential protein profiles, functional enrichment analysis, and protein–protein interaction network analysis were conducted based on TMT proteomics of 15 gingival tissues from healthy and periodontitis patients. DEPs correlating with periodontitis were screened using LASSO regression. We constructed a new diagnostic model using an artificial neural network (ANN) and verified its efficacy based on periodontitis transcriptomics datasets (GSE10334 and GSE16134). Western blotting validated expression levels of hub DEPs. TMT proteomics revealed 5658 proteins and 115 DEPs, and the 115 DEPs are closely related to inflammation and immune activity. Nine hub DEPs were screened by LASSO, and the ANN model distinguished healthy from periodontitis patients. The model showed satisfactory classification ability for both training (AUC=0.972) and validation (AUC=0.881) cohorts by ROC analysis. Expression levels of the 9 hub DEPs were validated and consistent with TMT proteomics quantitation. Our work reveals that nine hub DEPs in gingival tissues are closely related to the occurrence and progression of periodontitis and are potential signature molecules involved in periodontitis.