A functional AT/G polymorphism in the 5'-untranslated region (UTR) of SETDB2 in the IgE locus on human chromosome 13q14

The immunoglobulin E (IgE)-associated locus on human chromosome 13q14 influencing asthma-related traits contains the genes PHF11 and SETDB2. SETDB2 is located in the same linkage disequilibrium region as PHF11 and polymorphisms within SETDB2 have been shown to associate with total serum IgE levels. In this report, we sequenced the 15 exons of SETDB2 and identified a single previously ungenotyped mutation (AT/G, rs386770867) in the 5′-untranslated region of the gene. The polymorphism was found to be significantly associated with serum IgE levels in our asthma cohort (P=0.0012). Electrophoretic mobility shift assays revealed that the transcription factor Ying Yang 1 binds to the AT allele, whereas SRY (Sex determining Region Y) binds to the G allele. Allele-specific transcription analysis (allelotyping) was performed in 35 individuals heterozygous for rs386770867 from a panel of 200 British families ascertained through probands with severe stage 3 asthma. The AT allele was found to be significantly overexpressed in these individuals (P=1.26 × 10(−21)). A dual-luciferase assay with the pGL3 luciferase reporter gene showed that the AT allele significantly affects transcriptional activities. Our results indicate that the IgE-associated AT/G polymorphism (rs386770867) regulates transcription of SETDB2

The Influence of Radiographic Phenotype and Smoking Status on Peripheral Blood Biomarker Patterns in Chronic Obstructive Pulmonary Disease

Background: Chronic obstructive pulmonary disease (COPD) is characterized by both airway remodeling and parenchymal destruction. The identification of unique biomarker patterns associated with airway dominant versus parenchymal dominant patterns would support the existence of unique phenotypes representing independent biologic processes. A cross-sectional study was performed to examine the association of serum biomarkers with radiographic airway and parenchymal phenotypes of COPD. Methodology/Principal Findings: Serum from 234 subjects enrolled in a CT screening cohort was analyzed for 33 cytokines and growth factors using a multiplex protein array. The association of serum markers with forced expiratory volume in one second percent predicted (FEV1%) and quantitative CT measurements of airway thickening and emphysema was assessed with and without stratification for current smoking status. Significant associations were found with several serum inflammatory proteins and measurements of FEV1%, airway thickening, and parenchymal emphysema independent of smoking status. The association of select analytes with airway thickening and emphysema was independent of FEV1%. Furthermore, the relationship between other inflammatory markers and measurements of physiologic obstruction or airway thickening was dependent on current smoking status. Conclusions/Significance: Airway and parenchymal phenotypes of COPD are associated with unique systemic serum biomarker profiles. Serum biomarker patterns may provide a more precise classification of the COPD syndrome, provide insights into disease pathogenesis and identify targets for novel patient-specific biological therapies. © 2009 Bon et al

Genes to Diseases (G2D) Computational Method to Identify Asthma Candidate Genes

Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay−Lac-St-Jean (SLSJ) asthmatic familial collection (n = 609) to identify candidate genes located in two suggestive loci shown to be linked with asthma (6q26) and atopy (10q26.3), and presenting differential parent-of-origin effects. This approach combined gene selection based on the G2D data mining analysis of the bibliographic and protein public databases, or according to the genes already known to be associated with the same or a similar phenotype. Ten genes (LPA, NOX3, SNX9, VIL2, VIP, ADAM8, DOCK1, FANK1, GPR123 and PTPRE) were selected for a subsequent association study performed in a large SLSJ sample (n = 1167) of individuals tested for asthma and atopy related phenotypes. Single nucleotide polymorphisms (n = 91) within the candidate genes were genotyped and analysed using a family-based association test. The results suggest a protective association to allergic asthma for PTPRE rs7081735 in the SLSJ sample (p = 0.000463; corrected p = 0.0478). This association has not been replicated in the Childhood Asthma Management Program (CAMP) cohort. Sequencing of the regions around rs7081735 revealed additional polymorphisms, but additional genotyping did not yield new associations. These results demonstrate that the G2D tool can be useful in the selection of candidate genes located in chromosomal regions linked to a complex trait

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams

Inhibition of the Nuclear Import of Cubitus Interruptus by Roadkill in the Presence of Strong Hedgehog Signal

Hedgehog (Hh) signalling plays an important role in various developmental processes by activating the Cubitus interruptus (Ci)/Glioblastoma (Gli) family of transcription factors. In the process of proper pattern formation, Ci activity is regulated by multiple mechanisms, including processing, trafficking, and degradation. However, it remains elusive how Ci distinctly recognizes the strong and moderate Hh signals. Roadkill (Rdx) induces Ci degradation in the anterior region of the Drosophila wing disc. Here, we report that Rdx inhibited Ci activity by two different mechanisms. In the region abutting the anterior/posterior boundary, which receives strong Hh signal, Rdx inhibited the nuclear import of Ci by releasing importin α3 from Ci. In this region, Rdx negatively regulated the expression of transcription factor Knot/Collier. In farther anterior regions receiving moderate levels of Hh signal, Rdx induced Ci degradation, as reported previously. Thus, two different mechanisms by which Rdx negatively regulates Ci may play an important role in the fine-tuning of Hh responses

The Tumor Microenvironment: The Making of a Paradigm

What has been will be again, what has been done will be done again; there is nothing new under the su