Genomic/ Proteomic/ Metabonomic Profiling in Chronic Obstructive Pulmonary Disease (COPD)

A Non Interventional Study to Asses the Utility of Genomic/ Proteomic/ Metabonomic Profiling Approaches to the Classification and Pathological Basis of Inflammatory Lung Disease in Smokers, and Ex-smokers vs. Non-smokers and Asthmatics

Status

Withdrawn

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT00655694

Enrollment

Registered

2008-04-10

Start date

2005-01-31

Completion date

2007-09-30

Last updated

2019-07-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Pulmonary Disease, Chronic Obstructive

Keywords

COPD, smokers, healthy volunteers

Brief summary

Chronic obstructive pulmonary disease (COPD) is a chronic disease characterized by progressive airflow obstruction, chronic cough and dyspnoea in advanced stages. We hope to develop a better understanding of lung disease. Information from these studies will only be used for research purposes, to help develop safer and more effective treatments for asthma and COPD.

Detailed description

Techniques such as genomics, proteomics and metabonomics, Technologies that aim to identify and quantify the dynamic set of all small molecules and metabolites present in an organism or a biological sample, offer the prospect of efficiently distinguishing individuals with particular diseases. The advantages of proteomics and metabonomics is that it can be carried out on a standard preparation of serum, plasma or urine, circumventing the need for specialist preparation of cellular mRNA required for genomics This methodology is based on mass spectrometry (MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR) to analyze metabolites. High-performance liquid chromatography (HPLC) may also be applied. Several peak alignment algorithms have been developed to match the chromatograms before applying pattern recognition. Based on the pattern recognition, several potential biomarkers may be found and further identified by MS.. Finally, a number of potential biomarkers will be identified for distinguishing asthma and COPD.

Interventions

PROCEDUREsputum, blood, urine, exhaled breath, lung function

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

35 Years to No maximum

Inclusion criteria

* Inclusion Criteria - Healthy non-smokers * Non-smoking volunteer aged 40 -75 years (age matched to COPD patients) * Normal spirometry (FEV1/FVC ratio \>70% and FEV1\>80% predicted) * Subjects are able to give informed consent Inclusion Criteria-COPD patients (stage 2-3 according to the GOLD guidelines) * Current and/or ex-smokers with no less than 10 pack-year smoking history aged 40-75 years * 30% FEV1 \< 80% of predicted (the upper value is a postbronchodilator value) * FEV1/FVC \< 70% * Stable COPD (no chest infection requiring antibiotics and/ or oral steroids in the past 2 months) * Long-acting beta2-agonists and long-acting antimuscarinic bronchodilators need to be stopped at least 8 hours before the study visit * The subjects are able to give informed consent * Inclusion Criteria - healthy smokers * Current smokers aged 40 -75 years (age matched to COPD patients) * Normal spirometry (normal FEV1/FVC ratio \>70% and FEV1\>80% predicted) * Subjects are able to give informed consent * Inclusion Criteria - asthmatics * Non-smoking asthma patients aged 40 -75 years (age matched to COPD patients) * Normal spirometry (normal FEV1/FVC ratio \>70% and FEV1\>80% predicted) * Subjects are able to give informed consent

Exclusion criteria

Countries

United Kingdom

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026