Adam33 polymorphisms are associated with COPD and lung function in long-term tobacco smokers

<p>Abstract</p> <p>Background</p> <p>Variation in ADAM33 has been shown to be important in the development of asthma and altered lung function. This relationship however, has not been investigated in the population susceptible to COPD; long term tobacco smokers. We evaluated the association between polymorphisms in ADAM33 gene with COPD and lung function in long term tobacco smokers.</p> <p>Methods</p> <p>Caucasian subjects, at least 50 year old, who smoked ≥ 20 pack-years (n = 880) were genotyped for 25 single nucleotide polymorphisms (SNPs) in ADAM33. COPD was defined as an FEV1/FVC ratio < 70% and percent-predicted (pp)FEV1 < 75% (n = 287). The control group had an FEV1/FVC ratio ≥ 70% and ppFEV₁≥ 80% (n = 311) despite ≥ 20 pack years of smoking. Logistic and linear regressions were used for the analysis. Age, sex, and smoking status were considered as potential confounders.</p> <p>Results</p> <p>Five SNPs in ADAM33 were associated with COPD (Q-1, intronic: p < 0.003; S1, Ile → Val: p < 0.003; S2, Gly → Gly: p < 0.04; V-1 intronic: p < 0.002; V4, in 3' untranslated region: p < 0.007). Q-1, S1 and V-1 were also associated with ppFEV1, FEV1/FVC ratio and ppFEF25–75 (p values 0.001 – 0.02). S2 was associated with FEV1/FVC ratio (p < 0.05). The association between S1 and residual volume revealed a trend toward significance (p value < 0.07). Linkage disequilibrium and haplotype analyses suggested that S1 had the strongest degree of association with COPD and pulmonary function abnormalities.</p> <p>Conclusion</p> <p>Five SNPs in ADAM33 were associated with COPD and lung function in long-term smokers. Functional studies will be needed to evaluate the biologic significance of these polymorphisms in the pathogenesis of COPD.</p

Positive Association between Aspirin-Intolerant Asthma and Genetic Polymorphisms of FSIP1: a Case-Case Study

<p>Abstract</p> <p>Background</p> <p>Aspirin-intolerant asthma (AIA), which is caused by non-steroidal anti-inflammatory drugs (NSAIDs) such as aspirin, causes lung inflammation and reversal bronchi reduction, leading to difficulty in breathing. Aspirin is known to affect various parts inside human body, ranging from lung to spermatogenesis. <it>FSIP1</it>, also known as <it>HDS10</it>, is a recently discovered gene that encodes fibrous sheath interacting protein 1, and is regulated by amyloid beta precursor protein (APP). Recently, it has been reported that a peptide derived from APP is cleaved by α disintegrin and metalloproteinase 33 (<it>ADAM33</it>), which is an asthma susceptibility gene. It has also been known that the <it>FSIP1 </it>gene is expressed in airway epithelium.</p> <p>Objectives</p> <p>Aim of this study is to find out whether <it>FSIP1 </it>polymorphisms affect the onset of AIA in Korean population, since it is known that AIA is genetically affected by various genes.</p> <p>Methods</p> <p>We conducted association study between 66 single nucleotide polymorphisms (SNPs) of the <it>FSIP1 </it>gene and AIA in total of 592 Korean subjects including 163 AIA and 429 aspirin-tolerant asthma (ATA) patients. Associations between polymorphisms of <it>FSIP1 </it>and AIA were analyzed with sex, smoking status, atopy, and body mass index (BMI) as covariates.</p> <p>Results</p> <p>Initially, 18 SNPs and 4 haplotypes showed associations with AIA. However, after correcting the data for multiple testing, only one SNP showed an association with AIA (corrected <it>P</it>-value = 0.03, OR = 1.63, 95% CI = 1.23-2.16), showing increased susceptibility to AIA compared with that of ATA cases. Our findings suggest that <it>FSIP1 </it>gene might be a susceptibility gene for aspirin intolerance in asthmatics.</p> <p>Conclusion</p> <p>Although our findings did not suggest that SNPs of <it>FSIP1 </it>had an effect on the reversibility of lung function abnormalities in AIA patients, they did show significant evidence of association between the variants in <it>FSIP1 </it>and AIA occurrence among asthmatics in a Korean population.</p

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

Role of ADAM and ADAMTS metalloproteinases in airway diseases

Lungs are exposed to the outside environment and therefore to toxic and infectious agents or allergens. This may lead to permanent activation of innate immune response elements. A Disintegrin And Metalloproteinases (ADAMs) and ADAMs with Thrombospondin motifs (ADAMTS) are proteinases closely related to Matrix Metalloproteinases (MMPs). These multifaceted molecules bear metalloproteinase and disintegrin domains endowing them with features of both proteinases and adhesion molecules. Proteinases of the ADAM family are associated to various physiological and pathological processes and display a wide spectrum of biological effects encompassing cell fusion, cell adhesion, "shedding process", cleavage of various substrates from the extracellular matrix, growth factors or cytokines... This review will focus on the putative roles of ADAM/ADAMTS proteinases in airway diseases such as asthma and COPD

Water Flooding Performance Evaluation Using Percolation Theory

Water flooding is a well-known secondary mechanism for improving oil recovery. Conventional approach to evaluate the performance of a water flooding process (e.g. breakthrough and post breakthrough behavior) is to establish a reliable geological reservoir model, upscale it, and then perform flow simulations. To evaluate the uncertainty in the breakthrough time or post breakthrough behavior, this procedure has to be repeated for many realizations of the geological model, which takes many hours of CPU time. Moreover, during the early stage of reservoir life, when data is scare, breakthrough and post breakthrough time behavior prediction are usually based on analogues or rules of thumb. Alternative statistical approach is to use percolation theory to predict breakthrough and post breakthrough bahavior. The main contribution is to evaluate the applicability of the existing scaling laws of the breakthrough time by the numerical flow simulation results using the Burgan formation dataset of Norouz offshore oilfield in the south of Iran. Moreover, we extend the scaling to the post breakthrough behavior. There is good agreement between the predictions from the percolation based expressions and the numerical simulation results. Moreover, the prediction from the scaling law took a fraction of a second of CPU times (as it only needs some algebraic calculations) compared with many hours required for the conventional numerical simulations