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Relationship Between Metabolic Profile and Clinical Phenotype in Chronic Obstructive Pulmonary Disease

P

Peking University

Status

Completed

Conditions

Chronic Obstructive Pulmonary Disease

Study type

Observational

Funder types

Other

Identifiers

NCT03310177
Metabolomcs-HB

Details and patient eligibility

About

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.

Full description

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.

Enrollment

167 patients

Sex

Male

Ages

40 to 80 years old

Volunteers

No Healthy Volunteers

Inclusion and exclusion criteria

IInclusion Criteria:

  1. males aged 40-80;
  2. diagnosed with COPD according to the GOLD guidelines;
  3. clinically stable patients without medication changes or exacerbation in two months;
  4. smoking history of more than 10 pack years

Exclusion Criteria:

  1. diagnosed with unstable cardiovascular diseases, significant renal or hepatic dysfunction or mental incompetence;
  2. diagnosed with asthma, active pulmonary tuberculosis, diffuse panbronchiolitis, cystic fibrosis, clinically significant bronchiectasis, exacerbation of COPD or pneumonia in two months;
  3. prescribed immunosuppressive medications.

Trial design

167 participants in 2 patient groups

COPD
Description:
The smokers who are diagnosed as chronic obstructive pulmonary disease according to GOLD guideline.
healthy control
Description:
The healthy controls without chronic obstructive pulmonary disease

Trial contacts and locations

1

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Data sourced from clinicaltrials.gov

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