Peking University Third Hospital
Beijing, Beijing Municipality, 100191, China
NCT Number: NCT03310177
Despite the high prevalence of chronic obstructive pulmonary disease (COPD), there continues to be a large gap in our understanding of disease pathogenesis and mechanisms accounting for large variability in disease phenotype. Untargeted metabolomics is an ideal approach to uncover the metabolic basis of disease, as well as discover unique drug target opportunities aimed at these nodal metabolic drivers of disease. There are very limited data from metabolomics studies from plasma/serum and exhaled breath condensate that suggest certain metabolic pathways or metabolites might predict the presence and/or severity of COPD phenotypes.
Here, the investigators hope to generate comprehensive, compartment specific (blood and lung) metabolite profiles that will be correlated with various clinical phenotypes of COPD, using a complementary approach of untargeted nuclear magnetic resonance (NMR) and liquid chromatography (LC)- mass spectroscopy (MS) -based metabolomics.
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Notify Me40 year–80 year
Male
Observational
Beijing, Beijing Municipality, 100191, China
Despite the high prevalence of chronic obstructive pulmonary disease (COPD), there continues to be a large gap in our understanding of disease pathogenesis and mechanisms accounting for large variability in disease phenotype. Untargeted metabolomics is an ideal approach to uncover the metabolic basis of disease, as well as discover unique drug target opportunities aimed at these nodal metabolic drivers of disease. There are very limited data from metabolomics studies from plasma/serum and exhaled breath condensate that suggest certain metabolic pathways or metabolites might predict the presence and/or severity of COPD phenotypes.
The investigators hypothesize that: 1) smokers with COPD will have a metabolomics signature that is distinct from healthy non-COPD smokers; 2) this signature will be associated with clinically relevant manifestations of disease (e.g., GOLD classification, PFT).
The availability of biosamples from a well-characterized population of smokers with and without COPD, combined with our established in-house metabolomics expertise, will robustly allow to test these novel hypotheses. The investigators hope to generate comprehensive, compartment specific (blood and lung) metabolite profiles that will be correlated with various clinical phenotypes of COPD, using a complementary approach of untargeted nuclear magnetic resonance (NMR) and liquid chromatography (LC)- mass spectroscopy (MS) -based metabolomics. Moreover, this strategy may identify previously unrecognized metabolic pathways that are dysregulated in COPD. Collectively, these data will be used to direct a prospective clinical study to determine the association between metabolomics signatures and clinical outcomes.
Only the study team can determine whether someone qualifies for participation.
IInclusion Criteria:
Exclusion criteria
Time frame: 3 months
The study is aimed to investigate the relationship between the metabolites and the progress of lung function in COPD
Time frame: 3 months
The association between metabolites and emphysema is also investigated
Time frame: 3 months
The association between metabolites and inflammatory mediators is also investigated
Peking University Third Hospital
Other
Compartmental Analysis of Metabolite Profiles Associated With Disease Phenotype in Smokers With and Without Chronic Obstructive Pulmonary Disease
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