Integrated analysis of DNA methylation and gene expression profiles identified S100A9 as a potential biomarker in ulcerative colitis

Systematic analysis and characterization of long non-coding RNA genes in inflammatory bowel disease

The cases of inflammatory bowel disease (IBD) are increasing rapidly around the world. Due to the multifactorial causes of IBD, there is an urgent need to understand the pathogenesis of IBD. As such, the usage of high-throughput techniques to profile genetic mutations, microbiome environments, transcriptome and proteome (e.g. lipidome) is increasing to understand the molecular changes associated with IBD, including two major etiologies of IBD: Crohn disease (CD) and ulcerative colitis (UC). In the case of transcriptome data, RNA sequencing (RNA-seq) technique is used frequently. However, only protein-coding genes are analyzed, leaving behind all other RNAs, including non-coding RNAs (ncRNAs) to be unexplored. Among these ncRNAs, long non-coding RNAs (lncRNAs) may hold keys to understand the pathogenesis of IBD as lncRNAs are expressed in a cell/tissue-specific manner and dysregulated in a disease, such as IBD. However, it is rare that RNA-seq data are analyzed for lncRNAs. To fill this gap in knowledge, we re-analyzed RNA-seq data of CD and UC patients compared with the healthy donors to dissect the expression profiles of lncRNA genes. As inflammation plays key roles in the pathogenesis of IBD, we conducted loss-of-function experiments to provide functional data of IBD-specific lncRNA, lung cancer associated transcript 1 (LUCAT1), in an in vitro model of macrophage polarization. To further facilitate the lncRNA research in IBD, we built a web database, IBDB (https://ibd-db.shinyapps.io/IBDB/), to provide a one-stop-shop for expression profiling of protein-coding and lncRNA genes in IBD patients compared with healthy donors.

Epigenetic Insights Into Necrotizing Enterocolitis: Unraveling Methylation-Regulated Biomarkers

Necrotizing enterocolitis (NEC) is a multifactorial gastrointestinal disease with high morbidity and mortality among premature infants. This study aimed to identify novel methylation-regulated biomarkers in NEC intestinal tissue through multiomics analysis. We analyzed DNA methylation and transcriptome datasets from ileum and colon tissues of patients with NEC. We identify methylation-related differential genes (MrDEGs) based on the rule that the degree of methylation in the promoter region is inversely proportional to RNA transcription. These MrDEGs included ADAP1, GUCA2A, BCL2L14, FUT3, MISP, USH1C, ITGA3, UNC93A and IL22RA1. Single-cell data revealed that MrDEGs were mainly located in the intestinal epithelial part of intestinal tissue. These MrDEGs were verified through Target gene bisulfite sequencing and RT-qPCR. We successfully identified and verified the ADAP1, GUCA2A, IL22RA1 and MISP, primarily expressed in intestinal epithelial villus cells through single-cell data. Through single-gene gene set enrichment analysis, we found that these genes participate mainly in the pathological process of T-cell differentiation and the suppression of intestinal inflammation in NEC. This study enhances our understanding of the pathogenesis of NEC and may promote the development of new precision medicine methods for NEC prediction and diagnosis.

Novel biomarkers related to oxidative stress and immunity in chronic kidney disease

Introduction

The incidence of chronic kidney disease (CKD) has been increasing in recent years, gradually becoming a global health crisis. Due to limited treatment options, novel molecular pathways are urgently required to advance the treatment and diagnosis of CKD.

Materials and methods

The characteristics of differentially expressed genes (DEGs) in CKD patients were analyzed using Gene Expression Omnibus (GEO) database, and genes related to oxidative stress were retrieved from the Genecard database. Subsequently, a comprehensive approach was applied, including immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis, to identify hub genes among differentially expressed immune-related oxidative stress genes (DEIOSGs). Validation of hub genes was performed using an external data set, and diagnostic potential capability was evaluated through receiver operating curve (ROC) analysis. In animal experiments, the expression of hub genes in CKD was confirmed by inducing a CKD model through a 5/6 nephrectomy procedure. Finally, the relationship between these hub genes and clinical characteristics were assessed using the Nephroseq v5 database.

Results

29 DEIOSGs were identified by comprehensive bioinformatics analysis. PPI analysis screened the hub genes NCF2, S100A9, and SELL. ROC analysis demonstrated excellent diagnostic efficacy. Further validation from other databases and animal experiments confirmed a substantial upregulation in the expression of hub genes in CKD. Additionally, clinical correlation analysis established a clear link between hub gene expression and renal function deterioration.

Conclusions

Our study confirms NCF2, S100A9, and SELL as diagnostic biomarkers associated with immune response and oxidative stress in CKD, suggesting their potential as novel targets for CKD diagnosis and treatment.

Identification of immune-related hub genes contributing to the pathogenesis, diagnosis, and remission of ulcerative colitis by integrated bioinformatic analyses

The inflammatory disease ulcerative colitis (UC) is multifaceted, immune-mediated, chronic, and relapsing, which is considered to be mainly driven by dysregulated mucosal immune response. The remission of the inflammatory response is a marker of mucosal healing, relating to the low risk of hospitalizations, colorectal cancer, and colectomy. In spite of this, it is still unclear what the key immunological mechanism is which contributes to UC. Here, we explored the immune mechanism and related key genes underlying the state of inflammation in UC. Co-expression networks were constructed based on the expression profiles of immune-related genes in GSE179285. Using Weighted Gene Co-expression Network Analysis and Protein-protein interactions analysis, common hub genes were identified in the module of interest. Then, screening of real hub genes, significantly differentially expressing in inflamed UC, was carried out by Differential Expression Genes Analysis of GSE75214, GSE53306, and GSE6731datasets and immunohistochemistry of clinical samples. The diagnosis Capacity of the hub gene was identified by "glm" function in R. The potential key immune-related mechanisms were investigated using functional enrichment analysis and gene set enrichment analysis (GSEA). Bioinformatics tools were used to predict potential upstream transcription factors (TF), including the UCSC genome browser, correlation analyses, and JASPAR browser. The analysis revealed the blue module, consisting of 227 immune-related genes, showed the highest correlation with inflamed UC. And then, forty-three common candidates were distinguished. S100A9 was identified within the key module as a real hub gene with good diagnostic performance. The immune genes in the blue module were markedly enriched in the Cytokine-Cytokine receptor interaction. S100A9 most likely gets involved NOD-like receptor (NLR) signaling pathway. SPI1 showed the strongest likelihood to be the regulator. S100A9 was identified as the real immune-related hub gene for inflamed UC. Both diagnosis and remission may be aided by its high expression in the inflamed UC.

Epigenetic DNA methylation of Zbtb7b regulates the population of double-positive CD4+CD8+ T cells in ulcerative colitis

BACKGROUND AND AIMS

Ulcerative colitis (UC) is a heterogeneous disorder with complex pathogenesis. Therefore, in the present study, we aimed to assess genome-wide DNA methylation changes associated explicitly with the pathogenesis of UC.

METHODS

DNA methylation changes were identified by comparing UC tissues with healthy controls (HCs) from the GEO databases. The candidate genes were obtained and verified in clinical samples. Moreover, the underlying molecular mechanism related to Zbtb7b in the pathogenesis of UC was explored using the dextran sodium sulfate (DSS)-induced colitis model.

RESULTS

Bioinformatic analysis from GEO databases confirmed that Zbtb7b, known as Th-inducing POZ-Kruppel factor (ThPOK), was demethylated in UC tissues. Then, we demonstrated that Zbtb7b was in a hypo-methylation pattern through the DSS-induced colitis model (P = 0.0357), whereas the expression of Zbtb7b at the mRNA and protein levels was significantly up-regulated in the inflamed colonic tissues of UC patients (qRT-PCR, WB, IHC: P < 0.0001, P = 0.0079, P < 0.0001) and DSS-induced colitis model (qRT-PCR, WB, IHC: P < 0.0001, P = 0.0045, P = 0.0004). Moreover, the expression of Zbtb7b was positively associated with the degree of UC activity. Mechanically, over-expression of Zbtb7b might activate the maturation of CD4⁺T cells (FCM, IF: P = 0.0240, P = 0.0003) and repress the differentiation of double-positive CD4⁺CD8⁺T (DP CD4⁺CD8⁺T) cells (FCM, IF: P = 0.0247, P = 0.0118), contributing to the production of inflammatory cytokines, such as TNF-α (P = 0.0005, P = 0.0005), IL-17 (P = 0.0014, P = 0.0381), and IFN-γ (P = 0.0016, P = 0.0042), in the serum and colonic tissue of DSS-induced colitis model.

CONCLUSIONS

Epigenetic DNA hypo-methylation of Zbtb7b activated the maturation of CD4⁺T cells and repressed the differentiation of DP CD4⁺CD8⁺ T cells, resulting in the production of inflammatory cytokines and colonic inflammation in UC. Therefore, Zbtb7b might be a diagnostic and therapeutic biomarker for UC, and hypo-methylation might affect the biological function of Zbtb7b.

Identification of useful genes from multiple microarrays for ulcerative colitis diagnosis based on machine learning methods

Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease with an increasing incidence and prevalence worldwide. The diagnosis for UC mainly relies on clinical symptoms and laboratory examinations. As some previous studies have revealed that there is an association between gene expression signature and disease severity, we thereby aim to assess whether genes can help to diagnose UC and predict its correlation with immune regulation. A total of ten eligible microarrays (including 387 UC patients and 139 healthy subjects) were included in this study, specifically with six microarrays (GSE48634, GSE6731, GSE114527, GSE13367, GSE36807, and GSE3629) in the training group and four microarrays (GSE53306, GSE87473, GSE74265, and GSE96665) in the testing group. After the data processing, we found 87 differently expressed genes. Furthermore, a total of six machine learning methods, including support vector machine, least absolute shrinkage and selection operator, random forest, gradient boosting machine, principal component analysis, and neural network were adopted to identify potentially useful genes. The synthetic minority oversampling (SMOTE) was used to adjust the imbalanced sample size for two groups (if any). Consequently, six genes were selected for model establishment. According to the receiver operating characteristic, two genes of OLFM4 and C4BPB were finally identified. The average values of area under curve for these two genes are higher than 0.8, either in the original datasets or SMOTE-adjusted datasets. Besides, these two genes also significantly correlated to six immune cells, namely Macrophages M1, Macrophages M2, Mast cells activated, Mast cells resting, Monocytes, and NK cells activated (P  <  0.05). OLFM4 and C4BPB may be conducive to identifying patients with UC. Further verification studies could be conducted.

Macrophage-Biomimetic Nanoparticles Ameliorate Ulcerative Colitis through Reducing Inflammatory Factors Expression

Background and Aims

Inflammatory mediator S100A9 is dramatically elevated in ulcerative colitis and correlates with disease severity. S100A9 is a potential molecule to target for the treatment of colitis, but to date, there is no effective targeting method. The aim of this study was to develop a safe and effective nano-delivery system targeting S100A9 and to evaluate its therapeutic efficacy in ulcerative colitis mouse model.

Methods

We designed an oral nano-delivery system using poly (lactic acid-glycolic acid) (PLGA)-loaded S100A9 inhibitor tasquinimod to synthesize PLGA-TAS nanoparticles. TLR4-overexpressing macrophage membranes (MMs) were used to wrap the nanoparticles to make MM-PLGA-TAS, which allowed the nanoparticles to acquire the ability to specifically enrich the colitis region.

Results

MM-PLGA-TAS was endocytosed by inflammatory phenotype RAW264.7 cells in vitro and can efficiently enrich in inflamed mouse colitis tissue in vivo. A chemically induced ulcerative colitis mouse model was used to evaluate the therapeutic effect of oral MM-PLGA-TAS. MM-PLGA-TAS significantly alleviated the symptoms of ulcerative colitis, and mechanically, MM-PLGA-TAS achieved immunomodulatory and suppressive effects by reducing S100a9 and other cytokines in the colitis region.

Conclusion

We describe a convenient, orally targeted colitis drug delivery system that cures the disease in ulcerative colitis mice. This system substantially increases drug accumulation in inflamed colonic tissue, reduces the risk of systemic exposure, and is a promising therapeutic approach against ulcerative colitis.

Elevated systemic immune inflammation index level is associated with disease activity in ulcerative colitis patients

BACKGROUND

It has been confirmed that high Systemic immune-inflammation index (SII) levels usually indicate poor outcomes in various diseases, especially on malignancies. However, the clinical significance of the SII in ulcerative colitis (UC) patients is remain unclear. Therefore, the purpose of our paper is to analyze the levels of SII in UC patients and assess the relationship between the SII and disease activity.

MATERIALS AND METHODS

We studied 187 consecutive patients with UC and 185 age- and sex-matched healthy controls retrospectively. The Mayo scoring system was adopted to evaluate disease activity in UC patients. We collected clinical characteristics and laboratory parameters from hospital electronic medical records.

RESULTS

The SII levels were significantly higher in UC patients than those in healthy subjects (P < 0.001). Higher SII levels were observed in moderate and severe UC subgroups compared to mild or remission subgroups. Correlation analysis displayed that the SII levels were positively relatived with Mayo score (r = 0.469, P < 0.001), C reactive protein (CRP) (r = 0.480, P < 0.001), and erythrocyte sedimentation rate (ESR) (r = 0.336, P < 0.001), but negatively with haemoglobin (Hb) (r = -0.271, P < 0.001). A multiple linear regression analysis suggested that there was an independent correlation between Mayo score and SII (beta = 0.324, t = 4.241, P < 0.001). The receiver operating characteristic (ROC) curve revealed that the maximum area under the curve (AUC) was 0.711 (95% CI, 0.630-0.791, P < 0.001), and the cut-off value for diagnosing active UC was 485.95, the sensitivity was 0.641, and the specificity was 0.75.

CONCLUSIONS

We demonstrated that the SII was elevated significantly in UC patients and was closely related to the UC disease activity. In addition, the SII had a high discriminative capacity for active UC.

Epigenomic and transcriptomic analysis of chronic inflammatory diseases

Chronic inflammatory diseases (CIDs) have complex pathologies that result from aberrant and persistent immune responses. However, the precise triggers and mechanisms remain elusive. An important aspect of CID research focuses on epigenetics modifications, which regulate gene expression and provide a dynamic transcriptional response to inflammation. In recent years, mounting evidence has demonstrated an association between epigenomic and transcriptomic dysregulation and the phenotypes of CIDs. In particular, epigenetic changes at cis-regulatory elements have provided new insights for immune cell-specific alterations that contribute to disease etiology. Furthermore, the advancements in single-cell genomics provide novel solutions to cell type heterogeneity, which has long posed challenges for CID diagnosis and treatment. In this review, we discuss the current state of epigenomics research of CID and the insights derived from single-cell transcriptomic and epigenomic studies.