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: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:Expression data were generated on 136 subjects from the COPDGene® study using Affymetrix microarrays. Multiple linear regression with adjustment for covariates (gender, age, body mass index, family history, smoking status, pack years) was used to identify candidate genes and Ingenuity Pathway Analysis was used to identify candidate pathways. Candidate genes identified included those that play a role in the immune system, inflammatory responses, and sphingolipid metabolism. Many of our final candidate genes also show an association with related disease phenotypes such as emphysema, gas trapping, and 6-minute walk distance. 42 control subjects and 94 subjects with varying severity of COPD had PBMC gene expression profiles generated. All subjects are non-hispanic white, current or former smokers.
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 a heterogeneous disorder. COPD patients may have different clinical features, imaging characteristics and natural history. Multiple studies have investigated heterogeneity using statistical methods such as unsupervised clustering to define different subgroups of COPD based largely on clinical phenotypes. Some studies have performed clustering using genetic data or limited numbers of blood biomarkers. Our primary goal was to use proteomic data to find subtypes of COPD within clinically similar individuals. In the Treatment of Emphysema with a gamma-Selective Retinoid Agonist (TESRA) study, multiplex biomarker panels were run in serum samples collected prior to randomization. After implementing an algorithm to minimize missing values, the dataset included 396 COPD individuals and 87 biomarkers. Using hierarchical clustering, we identified 3 COPD subgroups, containing 267 (67.4%), 104 (26.3%), and 25 (6.3%) individuals, respectively. The third cluster had less emphysema on quantitative analysis of chest computed tomography scans (p=0.03) and worse disease-related quality of life based on the St. George's Respiratory Questionnaire (total score cluster 1: 45.6, cluster 2: 45.4, cluster 3: 56.6; p=0.01), despite similar levels of lung function impairment (forced expiratory volume in 1 second (49.2%, 49.2%, 48.2 % predicted, respectively). Enrichment analysis showed the biomarkers distinguishing cluster 3 mapped to platelet alpha granule and cell chemotaxis pathways. Thus, we identified a subgroup which has less emphysema but may have greater inflammation, which could be potentially targeted with anti-inflammatory therapies.
Project description:Expression data were generated on 136 subjects from the COPDGene® study using Affymetrix microarrays. Multiple linear regression with adjustment for covariates (gender, age, body mass index, family history, smoking status, pack years) was used to identify candidate genes and Ingenuity Pathway Analysis was used to identify candidate pathways. Candidate genes identified included those that play a role in the immune system, inflammatory responses, and sphingolipid metabolism. Many of our final candidate genes also show an association with related disease phenotypes such as emphysema, gas trapping, and 6-minute walk distance.
Project description:Blood eosinophils are a predictive biomarker of inhaled corticosteroid response in chronic obstructive pulmonary disease (COPD). We investigated blood eosinophil stability over 1 year using the Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2019 thresholds of < 100, 100- < 300 and ≥ 300 eosinophils/μL in 225 patients from the COPDMAP cohort. Blood eosinophils showed good stability (rho: 0.71, p < 0.001, ICC 0.84), and 69.3% of patients remained in the same eosinophil category at 1 year. 85.3% of patients with eosinophils < 100 cells/μL had stable counts. The majority of blood eosinophil counts remain stable over 1 year using the GOLD 2019 thresholds.
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:BACKGROUND:Spirometry is regarded as the gold standard for the diagnosis of COPD, yet the condition is widely underdiagnosed. Therefore, additional screening methods that are easy to perform and to interpret are needed. Recently, we demonstrated that low frequency ultrasound (LFU) may be helpful for monitoring lung diseases. The objective of this study was to evaluate whether LFU can be used to detect air trapping in COPD. In addition, we evaluated the ability of LFU to detect the effects of short-acting bronchodilator medication. METHODS:Seventeen patients with COPD and 9 healthy subjects were examined by body plethysmography and LFU. Ultrasound frequencies ranging from 1 to 40 kHz were transmitted to the sternum and received at the back during inspiration and expiration. The high pass frequency was determined from the inspiratory and the expiratory signals and their difference termed ?F. Measurements were repeated after inhalation of salbutamol. RESULTS:We found significant differences in ?F between COPD subjects and healthy subjects. These differences were already significant at GOLD stage 1 and increased with the severity of COPD. Sensitivity for detection of GOLD stage 1 was 83% and for GOLD stages worse than 1 it was 91%. Bronchodilator effects could not be detected reliably. CONCLUSIONS:We conclude that low frequency ultrasound is cost-effective, easy to perform and suitable for detecting air trapping. It might be useful in screening for COPD. TRIAL REGISTRATION:ClinicalTrials.gov: NCT01080924.