The effect of cigarette smoke exposure on the development of inflammation in lungs, gut and joints of TNFΔARE mice

The inflammatory cytokine TNF-alpha is a central mediator in many immune-mediated diseases, such as Crohn's disease (CD), spondyloarthritis (SpA) and chronic obstructive pulmonary disease (COPD). Epidemiologic studies have shown that cigarette smoking (CS) is a prominent common risk factor in these TNF-dependent diseases. We exposed TNF Delta ARE mice; in which a systemic TNF-alpha overexpression leads to the development of inflammation; to 2 or 4 weeks of air or CS. We investigated the effect of deregulated TNF expression on CS-induced pulmonary inflammation and the effect of CS exposure on the initiation and progression of gut and joint inflammation. Upon 2 weeks of CS exposure, inflammation in lungs of TNF Delta ARE mice was significantly aggravated. However, upon 4 weeks of CS-exposure, this aggravation was no longer observed. TNF Delta ARE mice have no increases in CD4+ and CD8+ T cells and a diminished neutrophil response in the lungs after 4 weeks of CS exposure. In the gut and joints of TNF Delta ARE mice, 2 or 4 weeks of CS exposure did not modulate the development of inflammation. In conclusion, CS exposure does not modulate gut and joint inflammation in TNF Delta ARE mice. The lung responses towards CS in TNF Delta ARE mice however depend on the duration of CS exposure

Evidence for Significant Overlap between Common Risk Variants for Crohn's Disease and Ankylosing Spondylitis

BACKGROUND: A multicenter genome-wide association scan for Crohn's Disease (CD) has recently reported 40 CD susceptibility loci, including 29 novel ones (19 significant and 10 putative). To gain insight into the genetic overlap between CD and ankylosing spondylitis (AS), these markers were tested for association in AS patients. PRINCIPAL FINDINGS: Two previously established associations, namely with the MHC and IL23R loci, were confirmed. In addition, rs2872507, which maps to a locus associated with asthma and influences the expression of the ORMDL3 gene in lymphoblastoid cells, showed a significant association with AS (p = 0.03). In gut biopsies of AS and CD patients, ORMDL3 expression was not significantly different from controls and no correlation was found with the rs2872507 genotype (Spearman's rho: -0.067). The distribution of p-values for the remaining 36 SNPs was significantly skewed towards low p-values unless the top 5 ranked SNPs (ORMDL3, NKX2-3, PTPN2, ICOSLG and MST1) were excluded from the analysis. CONCLUSIONS: Association analysis using risk variants for CD led to the identification of a new risk variant associated with AS (ORMDL3), underscoring a role for ER stress in AS. In addition, two known and five potentially relevant associations were detected, contributing to common susceptibility of CD and AS

COLOMBOS v3.0 : leveraging gene expression compendia for cross-species analyses

COLOMBOS is a database that integrates publicly available transcriptomics data for several prokaryotic model organisms. Compared to the previous version it has more than doubled in size, both in terms of species and data available. The manually curated condition annotation has been overhauled as well, giving more complete information about samples' experimental conditions and their differences. Functionality-wise cross-species analyses now enable users to analyse expression data for all species simultaneously, and identify candidate genes with evolutionary conserved expression behaviour. All the expression-based query tools have undergone a substantial improvement, overcoming the limit of enforced co-expression data retrieval and instead enabling the return of more complex patterns of expression behaviour. COLOMBOS is freely available through a web application at http://colombos.net/. The complete database is also accessible via REST API or downloadable as tab-delimited text files

Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering

<p>Abstract</p> <p>Background</p> <p>The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation, but the signaling mechanisms between irradiated and non-irradiated bystander cells are not fully understood. In this study, we measured a time-series of gene expression after α-particle irradiation and applied the Feature Based Partitioning around medoids Algorithm (FBPA), a new clustering method suitable for sparse time series, to identify signaling modules that act in concert in the response to direct irradiation and bystander signaling. We compared our results with those of an alternate clustering method, Short Time series Expression Miner (STEM).</p> <p>Results</p> <p>While computational evaluations of both clustering results were similar, FBPA provided more biological insight. After irradiation, gene clusters were enriched for signal transduction, cell cycle/cell death and inflammation/immunity processes; but only FBPA separated clusters by function. In bystanders, gene clusters were enriched for cell communication/motility, signal transduction and inflammation processes; but biological functions did not separate as clearly with either clustering method as they did in irradiated samples. Network analysis confirmed p53 and NF-κB transcription factor-regulated gene clusters in irradiated and bystander cells and suggested novel regulators, such as KDM5B/JARID1B (lysine (K)-specific demethylase 5B) and HDACs (histone deacetylases), which could epigenetically coordinate gene expression after irradiation.</p> <p>Conclusions</p> <p>In this study, we have shown that a new time series clustering method, FBPA, can provide new leads to the mechanisms regulating the dynamic cellular response to radiation. The findings implicate epigenetic control of gene expression in addition to transcription factor networks.</p