Project description:Diaphragm muscles in Chronic Obstructive Pulmonary Disease (COPD) patients undergo an adaptive fast to slow transformation that includes cellular adaptations. This project studies the signaling mechanisms responsible for this transformation. Keywords: other
Project description:An obesity paradox in chronic obstructive pulmonary disease (COPD), whereby overweight/obese individuals have improved survival, has been well-described. These studies have generally included smokers. It is unknown whether the paradox exists in individuals with COPD arising from factors other than smoking. Nonsmoking COPD is understudied yet represents some 25%-45% of the disease worldwide. To determine whether the obesity paradox differs between ever- and never-smokers with COPD, 1,723 adult participants with this condition were examined from 2 iterations of the National Health and Nutrition Examination Survey (1988-1994, 2007-2010), with mortality outcomes followed through December 2011. Using Cox proportional hazards models, adjusted for sociodemographic factors, lung function, and survey cycle, ever/never-smoking was found to modify the association between body mass index and hazard of death. Compared with normal-weight participants, overweight/obese participants had lower hazard of death among ever-smokers (for overweight, adjusted hazard ratio (aHR) = 0.56, 95% confidence interval (CI): 0.43, 0.74; for obesity, aHR = 0.66, 95% CI: 0.48, 0.92), but never-smokers did not (overweight, aHR = 1.41, 95% CI: 0.66, 3.03; obesity, aHR = 1.29, 95% CI: 0.48, 3.48). An obesity paradox appeared to be absent among never-smokers with COPD. This, to our knowledge, novel finding might be explained by pathophysiological differences between smoking-related and nonsmoking COPD or by smoking-associated methodological biases.
Project description:Investigation of whole genome gene expression level changes of the dynamic gene profiling of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD) on day1, 3 and 10, compared to the normal people and stable COPD patients. A five chip study using total RNA recovered from Peripheral Blood Mononuclear Cell of Peripheral Blood.Evaluating the dynamic gene profiling of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD) on day1, 3 and 10 after the hospital admission, to compared with healthy controls or patients with stable COPD. Slides were scanned at 5 μm/pixel resolution using an Axon GenePix 4000B scanner (Molecular Devices Corporation) piloted by GenePix Pro 6.0 software (Axon). Scanned images (TIFF format) were then imported into NimbleScan software (version 2.5) for grid alignment and expression data analysis. Expression data were normalized through quantile normalization and the Robust Multichip Average (RMA) algorithm included in the NimbleScan software. The Probe level (*_norm_RMA.pair) files and Gene level (*_RMA.calls) files were generated after normalization.
Project description:Investigation of whole genome gene expression level changes of the dynamic gene profiling of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD) on day1, 3 and 10, compared to the normal people and stable COPD patients.
Project description:Chronic obstructive pulmonary disease (COPD) is characterised by progressive airflow obstruction that is only partly reversible, inflammation in the airways, and systemic effects or comorbities. The main cause is smoking tobacco, but other factors have been identified. Several pathobiological processes interact on a complex background of genetic determinants, lung growth, and environmental stimuli. The disease is further aggravated by exacerbations, particularly in patients with severe disease, up to 78% of which are due to bacterial infections, viral infections, or both. Comorbidities include ischaemic heart disease, diabetes, and lung cancer. Bronchodilators constitute the mainstay of treatment: β(2) agonists and long-acting anticholinergic agents are frequently used (the former often with inhaled corticosteroids). Besides improving symptoms, these treatments are also thought to lead to some degree of disease modification. Future research should be directed towards the development of agents that notably affect the course of disease.
Project description:There is a growing realization that chronic obstructive pulmonary disease involves several processes present in aging and cellular senescence. The impact of these processes in the pathogenesis of the main manifestations is multiple, particularly in the propagation of a proinflammatory phenotype, loss of reparative potential, and amplification of oxidative stress, all ultimately leading to tissue damage. This review highlights salient aspects related to senescence discussed in the 2011 Aspen Lung Conference.
Project description:Recent therapeutic advances in the management of asthma have underscored the importance of eosinophilia and the role of pro-eosinophilic mediators such as IL-5 in asthma. Given that a subset of patients with COPD may display peripheral eosinophilia similar to what is observed in asthma, a number of recent studies have implied that eosinophilic COPD is a distinct entity. This review will seek to contrast the mechanisms of eosinophilia in asthma and COPD, the implications of eosinophilia for disease outcome, and review current data regarding the utility of peripheral blood eosinophilia in the management of COPD patients.
Project description:Identifying protein biomarkers for chronic obstructive pulmonary disease (COPD) has been challenging. Most previous studies have utilized individual proteins or pre-selected protein panels measured in blood samples. To identify COPD protein biomarkers by applying comprehensive mass spectrometry proteomics in lung tissue samples. We utilized mass spectrometry proteomic approaches to identify protein biomarkers from 152 lung tissue samples representing COPD cases and controls.
Project description:Measuring genome-wide changes in transcript abundance in circulating peripheral whole blood cells is a useful way to study disease pathobiology and may help elucidate biomarkers and molecular mechanisms of disease. The sensitivity and interpretability of analyses carried out in this complex tissue, however, are significantly affected by its heterogeneity. It is therefore desirable to quantify this heterogeneity, either to account for it or to better model interactions that may be present between the abundance of certain transcripts, some cell types and some indication. Accurate enumeration of the many component cell types that make up peripheral whole blood can be costly, however, and may further complicate the sample collection process. Many approaches have been developed to infer the composition of a sample from high-dimensional transcriptomic and, more recently, epigenetic data. These approaches rely on the availability of isolated expression profiles for the cell types to be enumerated. These profiles are platform-specific, suitable datasets are rare, and generating them is expensive. No such dataset exists on the Affymetrix Gene ST platform. We present a freely-available, and open-source, multiresponse Gaussian model capable of accurately inferring the composition of peripheral whole blood samples from Affymetrix Gene ST expression profiles. The model was developed on a cohort of patients with chronic obstructive pulmonary disease (COPD) and tested in chronic heart failure patients.