Significance of IL-1RA Polymorphism in Iranian Patients with Inflammatory Bowel Disease

Inflammatory factors, genetic variants, and predisposition for preterm birth

Preterm birth is a major clinical and public health challenge, with a prevalence of 11% worldwide. It is the leading cause of death in children younger than 5 years old and represents 70% of neonatal deaths and 75% of neonatal morbidity. Despite the clinical and public health significance, this condition's etiology is still unclear, and most of the cases are spontaneous. There are several known preterm birth risk factors, including inflammatory diseases and the genetic background, although the underlying molecular mechanisms are far from understood. The present review highlights the research advances on the association between inflammatory-related genes and the increased risk for preterm delivery. The most associated genetic variants are the TNFα rs1800629, the IL1α rs17561, and the IL1RN rs2234663. Moreover, many of the genes discussed in this review are also implicated in pathologies involving inflammatory or autoimmune systems, such as periodontal disease, bowel inflammatory disease, and autoimmune rheumatic diseases. This review presents evidence suggesting a common genetic background to preterm birth, autoimmune and inflammatory diseases susceptibility.

Identification of Differential Intestinal Mucosa Transcriptomic Biomarkers for Ulcerative Colitis by Bioinformatics Analysis

Background

Ulcerative colitis (UC) is a complicated disease caused by the interaction between genetic and environmental factors that affect mucosal homeostasis and triggers inappropriate immune response. The purpose of the study was to identify significant biomarkers with potential therapeutic targets and the underlying mechanisms.

Methods

The gene expression profiles of GSE48958, GSE73661, and GSE59071 are from the GEO database. Differentially expressed genes (DEGs) were screened by the GEO2R tool. Next, the Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Then, protein-protein interaction (PPI) was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING).

Results

There were a total of 128 common DEGs genes, including 86 upregulated genes enriched in extracellular space, regulation of inflammatory response, chemokine-mediated signaling pathway, response to lipopolysaccharide, and cell proliferation, while 42 downregulated genes enriched in the integral component of the membrane, the integral component of the plasma membrane, apical plasma membrane, symporter activity, and chloride channel activity. The KEGG pathway analysis results demonstrated that DEGs were particularly enriched in cytokine-cytokine receptor interaction, TNF signaling pathway, chemokine signaling pathway, pertussis, and rheumatoid arthritis. 18 central modules of the PPI networks were selected with Cytotype MCODE. Furthermore, 18 genes were found to significantly enrich in the extracellular space, inflammatory response, chemokine-mediated signaling pathway, TNF signaling pathway, regulation of cell proliferation, and immune response via reanalysis of DAVID.

Conclusion

The study identified DEGs, key target genes, functional pathways, and pathway analysis of UC, which may provide potential molecular targets and diagnostic biomarkers for UC.

The association between IL-1 family gene polymorphisms and colorectal cancer: A meta-analysis

BACKGROUND

Colorectal cancer (CRC) is a major public health problem given its high incidence and mortality. This study focuses on examining the associations between IL-1α, IL-1β, and IL-1RN polymorphisms and colorectal cancer susceptibility.

METHODS

A systematic literature search of PubMed, Embase, Web of Science, CNKI (China National Knowledge Infrastructure) and Wan Fang databases was conducted to identify relevant studies. Relevant data were extracted from the original included studies. The correlation was demonstrated based on the odds ratio (OR) and corresponding 95% confidence intervals (95% CIs). Publication bias was investigated by Egger's line regression test and Begg's funnel plot.

RESULTS

Eighteen independent studies involving 6218 cases and 10160 controls were eligible for this pooled analysis. Overall, the result revealed that the IL-1α rs3783553 polymorphism was significantly associated with an increased risk of CRC (G vs. C, OR = 1.02, 95% CI = 0.90-1.15, I² = 51%, P = 0.78; GG vs. CC, OR = 1.97, 95% CI = 1.04-3.74, I² = 70%, P = 0.04; GC vs. CC, OR = 1.75, 95% CI = 1.12-2.75, I² = 42%, P = 0.01; GG + GC vs. CC, OR = 1.85, 95% CI = 1.08-3.18, I² = 63%, P = 0.03; and GG vs. GC + CC, OR = 1.28, 95% CI = 1.04-1.58, I² = 39%, P = 0.02), and significance was also noted for IL-1RN VNTR under the dominant model (22 + 2L vs. LL, OR = 1.49, 95% CI = 1.01-2.19, I² = 77%, P = 0.045) and allelic contrast model (2 vs. L, OR = 1.28, 95% CI = 1.00-1.64, I² = 58.6%, P = 0.047). For IL-1β + 31C/T, significance was observed in the dominant model (CC + CT vs. TT, OR = 0.83, 95% CI = 0.69-0.99, I² = 52%, P = 0.034) and the heterozygous model (CT vs. TT, OR = 0.80, 95% CI = 0.65-0.98, I² = 60%, P = 0.04). For IL-1β + 511 C/T, a significant association was noted in four gene models (CT vs. TT, OR = 0.72, 95% CI = 0.63-0.83, I² = 0%, P < 0.001; CC + CT vs. TT, OR = 0.74, 95% CI = 0.65-0.84, I² = 0%, P < 0.001; CC vs. TT, OR = 0.77, 95% CI = 0.65-0.91, I² = 30.9%, P = 0.003; C vs. T, OR = 0.87, 95% CI = 0.80-0.95, I² = 38%, P = 0.001), but a significant relationship was not found in the recessive model (CC vs. CT + TT, OR = 1.09, 95% CI = 0.86-1.38, I² = 57.1%, P = 0.25). In addition, borderline statistical significance was noted between IL-1β + 3954 Ins/Del and CRC in the homozygous model, but no significance was identified for IL-1β + 3737 G/A, Il-1β + 1464 G/C, and IL-1RN + 2018 T/C under all five genetic models. In the subgroup analysis of ethnic groups, significant associations with CRC were found for IL-1β + 31 (CC vs. TT: OR = 0.82, 95% CI = 0.67-0.99, I² = 20.2%, P = 0.04; CT vs. TT: OR = 0.62, 95% CI = 0.47-0.82, I² = 0%, P < 0.001; CC + CT vs. TT: OR = 0.69, 95% CI = 0.55-0.87, I² = 29.7%, P = 0.001), IL-1β + 511 (CT vs. TT, OR = 0.65, 95% CI = 0.55-0.77, I² = 0%, P < 0.001; CC + CT vs. TT, OR = 0.67, 95% CI = 0.58-0.78, I² = 0%, P < 0.001; C vs. T, OR = 0.83, 95% CI = 0.75-0.92, I² = 49.6%, P < 0.001) and IL-1RN + 2018 T/C in the allelic contrast model (T vs. C, OR = 0.66, 95% CI = 0.44-0.98, I² = 0%, P = 0.04) among Asians but not in Caucasians. A significant association between IL-1β + 1464 G/C polymorphisms in Caucasians was observed under the recessive model (OR = 0.87, 95% CI = 0.77-0.98, I² = 45%, P = 0.03).

CONCLUSION

The current meta-analysis demonstrated that IL-1α rs3783553, IL-1β + 31C/T, IL-1β + 511C/T, and IL-1RN VNTR are critical genes for CRC susceptibility.

Differential Intestinal Mucosa Transcriptomic Biomarkers for Crohn's Disease and Ulcerative Colitis

Genetic research has shaped the inflammatory bowel disease (IBD) landscape identifying nearly two hundred risk loci. Nonetheless, the identified variants rendered only a partial success in providing criteria for the differential diagnosis between ulcerative colitis (UC) and Crohn's disease (CD). Transcript levels from affected intestinal mucosa may serve as tentative biomarkers for improving classification and diagnosis of IBD. The aim of our study was to identify gene expression profiles specific for UC and CD, in endoscopically affected and normal intestinal colonic mucosa from IBD patients. We evaluated a panel of 84 genes related to the IBD-inflammatory pathway on 21 UC and 22 CD paired inflamed and not inflamed mucosa and on age-matched normal mucosa from 21 non-IBD controls. Two genes in UC (CCL11 and MMP10) and two in CD (C4BPB and IL1RN) showed an upregulation trend in both noninflamed and inflamed mucosa compared to controls. Our results suggest that the transcript levels of CCL11, MMP10, C4BPB, and IL1RN are candidate biomarkers that could help in clinical practice for the differential diagnosis between UC and CD and could guide new research on future therapeutic targets.

A functional genomics predictive network model identifies regulators of inflammatory bowel disease

A major challenge in inflammatory bowel disease (IBD) is the integration of diverse IBD data sets to construct predictive models of IBD. We present a predictive model of the immune component of IBD that informs causal relationships among loci previously linked to IBD through genome-wide association studies (GWAS) using functional and regulatory annotations that relate to the cells, tissues, and pathophysiology of IBD. Our model consists of individual networks constructed using molecular data generated from intestinal samples isolated from three populations of patients with IBD at different stages of disease. We performed key driver analysis to identify genes predicted to modulate network regulatory states associated with IBD, prioritizing and prospectively validating 12 of the top key drivers experimentally. This validated key driver set not only introduces new regulators of processes central to IBD but also provides the integrated circuits of genetic, molecular, and clinical traits that can be directly queried to interrogate and refine the regulatory framework defining IBD.