Waiting in the wings: RUNX3 reveals hidden depths of immune regulation with potential implications for inflammatory bowel disease

CD30 co-stimulation drives differentiation of protective T cells during Mycobacterium tuberculosis infection

Control of Mycobacterium tuberculosis (Mtb) infection requires generation of T cells that migrate to granulomas, complex immune structures surrounding sites of bacterial replication. Here we compared the gene expression profiles of T cells in pulmonary granulomas, bronchoalveolar lavage, and blood of Mtb-infected rhesus macaques to identify granuloma-enriched T cell genes. TNFRSF8/CD30 was among the top genes upregulated in both CD4 and CD8 T cells from granulomas. In mice, CD30 expression on CD4 T cells is required for survival of Mtb infection, and there is no major role for CD30 in protection by other cell types. Transcriptomic comparison of WT and CD30-/- CD4 T cells from the lungs of Mtb-infected mixed bone marrow chimeric mice showed that CD30 directly promotes CD4 T cell differentiation and the expression of multiple effector molecules. These results demonstrate that the CD30 co-stimulatory axis is highly upregulated on granuloma T cells and is critical for protective T cell responses against Mtb infection.

Transcriptomic Context of RUNX3 Expression in Monocytes: A Cross-Sectional Analysis

The runt-related transcription factor 3 (RUNX3) regulates the differentiation of monocytes and their response to inflammation. However, the transcriptomic context of RUNX3 expression in blood monocytes remains poorly understood. We aim to learn about RUNX3 from its relationships within transcriptomes of bulk CD14+ cells in adults. This study used immunomagnetically sorted CD14+ cell gene expression microarray data from the Multi-Ethnic Study of Atherosclerosis (MESA, n = 1202, GSE56047) and the Correlated Expression and Disease Association Research (CEDAR, n = 281, E-MTAB-6667) cohorts. The data were preprocessed, subjected to RUNX3-focused correlation analyses and random forest modeling, followed by the gene ontology analysis. Immunity-focused differential ratio analysis with intermediary inference (DRAIMI) was used to integrate the data with protein-protein interaction network. Correlation analysis of RUNX3 expression revealed the strongest positive association for EVL (r_mean = 0.75, p_FDR-MESA = 5.37 × 10^-140, p_FDR-CEDAR = 5.52 × 10^-80), ARHGAP17 (r_mean = 0.74, p_FDR-MESA = 1.13 × 10^-169, p_FDR-CEDAR = 9.20 × 10^-59), DNMT1 (r_mean = 0.74, p_FDR-MESA = 1.10 × 10^-169, p_FDR-CEDAR = 1.67 × 10^-58), and CLEC16A (r_mean = 0.72, p_FDR-MESA = 3.51 × 10^-154, p_FDR-CEDAR = 2.27 × 10^-55), while the top negative correlates were C2ORF76 (r_mean = -0.57, p_FDR-MESA = 8.70 × 10^-94, p_FDR-CEDAR = 1.31 × 10^-25) and TBC1D7 (r_mean = -0.55, p_FDR-MESA = 1.36 × 10^-69, p_FDR-CEDAR = 7.81 × 10^-30). The RUNX3-associated transcriptome signature was involved in mRNA metabolism, signal transduction, and the organization of cytoskeleton, chromosomes, and chromatin, which may all accompany mitosis. Transcriptomic context of RUNX3 expression in monocytes hints at its relationship with cell growth, shape maintenance, and aspects of the immune response, including tyrosine kinases.

Immune cells and their related genes provide a new perspective on the common pathogenesis of ankylosing spondylitis and inflammatory bowel diseases

Background

The close relationship between ankylosing spondylitis (AS) and inflammatory bowel diseases (IBD) has been supported by many aspects, including but not limited to clinical manifestations, epidemiology and pathogenesis. Some evidence suggests that immune cells actively participated in the pathogenesis of both diseases. However, information on which cells are primarily involved in this process and how these cells mobilize, migrate and interact is still limited.

Methods

Datasets were downloaded from Gene Expression Omnibus (GEO) database. Common differentially expressed genes (coDEGs) were identified by package “limma”. The protein-protein interaction (PPI) network and Weighted Gene Co-Expression Network Analysis (WGCNA) were used to analyze the interactions between coDEGs. KEGG pathway enrichment analysis and inverse cumulative distribution function were applied to identify common differential pathways, while Gene Set Enrichment Analysis (GSEA) was used to confirm the significance. Correlation analysis between coDEGs and immune cells led to the identification of critical immune-cell-related coDEGs. The diagnostic models were established based on least absolute shrinkage and selection operator (LASSO) regression, while receiver operating characteristic (ROC) analysis was used to identify the ability of the model. Validation datasets were imported to demonstrate the significant association of coDEGs with specific immune cells and the capabilities of the diagnostic model.

Results

In total, 67 genes were up-regulated and 185 genes were down-regulated in both diseases. Four down-regulated pathways and four up-regulated pathways were considered important. Up-regulated coDEGs were firmly associated with neutrophils, while down-regulated genes were significantly associated with CD8+ T−cells and CD4+ T−cells in both AS and IBD datasets. Five up-regulated and six down-regulated key immue-cell-related coDEGs were identified. Diagnostic models based on key immue-cell-related coDEGs were established and tested. Validation datasets confirmed the significance of the correlation between coDEGs and specific immune cells.

Conclusion

This study provides fresh insights into the co-pathogenesis of AS and IBD. It is proposed that neutrophils and T cells may be actively involved in this process, however, in opposite ways. The immue-cell-related coDEGs, revealed in this study, may be relevant to their regulation, although relevant research is still lacking.

Expression levels of RUNX3 and FGFR2 in peripheral blood of severe acute pancreatitis and their clinical significance

Purpose

Severe acute pancreatitis (SAP) is a life-threatening inflammatory syndrome of the pancreas. This study aimed to analyze the clinical significance of runt-associated transcription factor 3 (RUNX3) and fibroblast growth factor receptor 2 (FGFR2) expression alterations in SAP.

Methods

This study included 18 SAP patients in Wuzhong People's Hospital from November 2019 to December 2021 and 18 healthy controls. RUNX3 and FGFR2 expression levels were determined by RT-quantitative PCR. Correlations between RUNX3/FGFR2 and sex, age, etiology, CRP, procalcitonin, AST, LDH, BUN, Acute Physiology and Chronic Health Evaluation II (APACHE II), Ranson score, Bedside Index for Severity in Acute Pancreatitis (BISAP) score, sequential organ failure assessment (SOFA), and modified computed tomography severity index (MCTSI) score were analyzed. Diagnostic values of RUNX3 and FGFR2 in SAP were analyzed using the receiver-operating characteristic curve. The binding of RUNX3 to FGFR2 was analyzed by chromatin immunoprecipitation.

Results

RUNX3 and FGFR2 were downregulated in peripheral blood of SAP patients. RUNX3 and FGFR2 were negatively correlated with CRP, procalcitonin, AST, LDH, BUN, APACHE II score, Ranson score, BISAP score, SOFA score, and MCTSI score. Sensitivity and specificity of RUNX3 level of <0.9650 for SAP diagnosis were 88.89% and 72.22%, respectively. Sensitivity and specificity of FGFR2 level of <0.8950 for SAP diagnosis were 66.67% and 83.33%, respectively. RUNX3 was enriched in the FGFR2 promoter and was positively correlated with FGFR2.

Conclusion

RUNX3 and FGFR2 were downregulated in peripheral blood of SAP patients and served as candidate biomarkers for SAP diagnosis. RUNX3 bound to the FGFR2 promoter to promote FGFR2 transcription.

Methylation of RUNX3 Promoter 2 in the Whole Blood of Children with Ulcerative Colitis

Ulcerative colitis (UC) results from a complex interplay between the environment, gut microbiota, host genetics, and immunity. Runt-related transcription factor 3 (RUNX3) regulates Th1/Th2 balance and, thus, the synthesis of cytokines and inflammation. We aimed to analyze the dependence of RUNX3 promoter 2 (P2) methylation level on: age, sex, body mass index (BMI), C-reactive protein (CRP), serum albumin, disease duration, Pediatric Ulcerative Colitis Activity Index (PUCAI), the Paris classification, and exposure to medications. This multicenter, cross-sectional study recruited hospitalized children with UC. Methylation of RUNX3 P2 was measured with methylation-sensitive restriction enzymes in the whole blood DNA. Sixty-four children were enrolled, with a mean age of 14.5 ± 2.8 years. Half of them were female (51.6%), and the average BMI Z-score was −0.44 ± 1.14. The mean methylation of RUNX3 P2 was 54.1 ± 13.3%. The methylation level of RUNX3 P2 did not correlate with age, sex, nutritional status, CRP, albumin, PUCAI, or the extent of colitis (Paris E1–E4). RUNX3 P2 methylation did not differ between patients recruited within two and a half months of diagnosis and children who had UC for at least a year. Current or past exposure to biologics, immunosuppressants, or steroids was not associated with RUNX3 P2 methylation. Methylation of RUNX3 promoter 2 in whole blood DNA does not seem to be associated with the characteristics of UC in children.